id stringlengths 9 13 | submitter stringlengths 4 48 | authors stringlengths 4 9.62k | title stringlengths 4 343 | comments stringlengths 2 480 ⌀ | journal-ref stringlengths 9 309 ⌀ | doi stringlengths 12 138 ⌀ | report-no stringclasses 277 values | categories stringlengths 8 87 | license stringclasses 9 values | orig_abstract stringlengths 27 3.76k | versions listlengths 1 15 | update_date stringlengths 10 10 | authors_parsed listlengths 1 147 | abstract stringlengths 24 3.75k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
q-bio/0605010 | Juliana Dias | Juliana R. Dias, Rodrigo F. Oliveira and Osame Kinouchi | Chaotic itinerancy, temporal segmentation and spatio-temporal
combinatorial codes | null | Physica D: Nonlinear Phenomena, Volume 237, Issue 1, p. 1-5 (2008) | 10.1016/j.physd.2007.06.021 | null | q-bio.NC | null | We study a deterministic dynamics with two time scales in a continuous state
attractor network. To the usual (fast) relaxation dynamics towards point
attractors (``patterns'') we add a slow coupling dynamics that makes the
visited patterns to loose stability leading to an itinerant behavior in the
form of punctuated equilibria. One finds that the transition frequency matrix
between patterns shows non-trivial statistical properties in the chaotic
itinerant regime. We show that mixture input patterns can be temporally
segmented by the itinerant dynamics. The viability of a combinatorial
spatio-temporal neural code is also demonstrated.
| [
{
"created": "Fri, 5 May 2006 14:19:16 GMT",
"version": "v1"
},
{
"created": "Thu, 18 May 2006 20:35:31 GMT",
"version": "v2"
}
] | 2010-06-10 | [
[
"Dias",
"Juliana R.",
""
],
[
"Oliveira",
"Rodrigo F.",
""
],
[
"Kinouchi",
"Osame",
""
]
] | We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors (``patterns'') we add a slow coupling dynamics that makes the visited patterns to loose stability leading to an itinerant behavior in the form of punctuated equilibria. One finds that the transition frequency matrix between patterns shows non-trivial statistical properties in the chaotic itinerant regime. We show that mixture input patterns can be temporally segmented by the itinerant dynamics. The viability of a combinatorial spatio-temporal neural code is also demonstrated. |
1902.08599 | Giulia De Bonis | Giulia De Bonis, Miguel Dasilva, Antonio Pazienti, Maria V.
Sanchez-Vives, Maurizio Mattia and Pier Stanislao Paolucci | Slow Waves Analysis Pipeline for extracting the Features of the
Bi-Modality from the Cerebral Cortex of Anesthetized Mice | 18 pages, 10 figures, 1 table | null | 10.3389/fnsys.2019.00070 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cortical slow oscillations are an emergent property of the cortical network,
a hallmark of low complexity brain states like sleep, and represent a default
activity pattern. Here, we present a methodological approach for quantifying
the spatial and temporal properties of this emergent activity. We improved and
enriched a robust analysis procedure that has already been successfully applied
to both in vitro and in vivo data acquisitions. We tested the new tools of the
methodology by analyzing the electrocorticography (ECoG) traces recorded from a
custom 32-channel multi-electrode array in wild-type isoflurane-anesthetized
mice. The enhanced analysis pipeline, named SWAP (Slow Waves Analysis
Pipeline), detects Up and Down states, enables the characterization of the
spatial dependency of their statistical properties, and supports the comparison
of different subjects. The SWAP is implemented in a data-independent way,
allowing its application to other data sets (acquired from different subjects,
or with different recording tools), as well as to the outcome of numerical
simulations. By using SWAP, we report statistically significant differences in
the observed slow oscillations (SO) across cortical areas and cortical sites.
Computing cortical maps by interpolating the features of SO acquired at the
electrode positions, we give evidence of gradients at the global scale along an
oblique axis directed from fronto-lateral towards occipito-medial regions,
further highlighting some heterogeneity within cortical areas. The results
obtained on spatial characterization of slow oscillations will be essential for
producing data-driven brain simulations and for triggering a discussion on the
role of, and the interplay between, the different regions in the cortex,
improving our understanding of the mechanisms of generation and propagation of
delta rhythms and, more generally, of cortical properties.
| [
{
"created": "Fri, 22 Feb 2019 18:27:51 GMT",
"version": "v1"
},
{
"created": "Fri, 8 Mar 2019 12:48:01 GMT",
"version": "v2"
}
] | 2021-11-09 | [
[
"De Bonis",
"Giulia",
""
],
[
"Dasilva",
"Miguel",
""
],
[
"Pazienti",
"Antonio",
""
],
[
"Sanchez-Vives",
"Maria V.",
""
],
[
"Mattia",
"Maurizio",
""
],
[
"Paolucci",
"Pier Stanislao",
""
]
] | Cortical slow oscillations are an emergent property of the cortical network, a hallmark of low complexity brain states like sleep, and represent a default activity pattern. Here, we present a methodological approach for quantifying the spatial and temporal properties of this emergent activity. We improved and enriched a robust analysis procedure that has already been successfully applied to both in vitro and in vivo data acquisitions. We tested the new tools of the methodology by analyzing the electrocorticography (ECoG) traces recorded from a custom 32-channel multi-electrode array in wild-type isoflurane-anesthetized mice. The enhanced analysis pipeline, named SWAP (Slow Waves Analysis Pipeline), detects Up and Down states, enables the characterization of the spatial dependency of their statistical properties, and supports the comparison of different subjects. The SWAP is implemented in a data-independent way, allowing its application to other data sets (acquired from different subjects, or with different recording tools), as well as to the outcome of numerical simulations. By using SWAP, we report statistically significant differences in the observed slow oscillations (SO) across cortical areas and cortical sites. Computing cortical maps by interpolating the features of SO acquired at the electrode positions, we give evidence of gradients at the global scale along an oblique axis directed from fronto-lateral towards occipito-medial regions, further highlighting some heterogeneity within cortical areas. The results obtained on spatial characterization of slow oscillations will be essential for producing data-driven brain simulations and for triggering a discussion on the role of, and the interplay between, the different regions in the cortex, improving our understanding of the mechanisms of generation and propagation of delta rhythms and, more generally, of cortical properties. |
2109.13198 | Christos Giotis | Christos Giotis, Alexander Serb, Vasileios Manouras, Spyros
Stathopoulos and Themis Prodromakis | Palimpsest Memories Stored in Memristive Synapses | 12 pages, 4 figures | null | null | null | q-bio.NC cs.AR cs.ET | http://creativecommons.org/licenses/by/4.0/ | Biological synapses store multiple memories on top of each other in a
palimpsest fashion and at different timescales. Palimpsest consolidation is
facilitated by the interaction of hidden biochemical processes that govern
synaptic efficacy during varying lifetimes. This arrangement allows idle
memories to be temporarily overwritten without being forgotten, in favour of
new memories utilised in the short-term. While embedded artificial intelligence
can greatly benefit from such functionality, a practical demonstration in
hardware is still missing. Here, we show how the intrinsic properties of
metal-oxide volatile memristors emulate the hidden processes that support
biological palimpsest consolidation. Our memristive synapses exhibit an
expanded doubled capacity which can protect a consolidated long-term memory
while up to hundreds of uncorrelated short-term memories temporarily overwrite
it. The synapses can also implement familiarity detection of previously
forgotten memories. Crucially, palimpsest operation is achieved automatically
and without the need for specialised instructions. We further demonstrate a
practical adaptation of this technology in the context of image vision. This
showcases the use of emerging memory technologies to efficiently expand the
capacity of artificial intelligence hardware towards more generalised learning
memories.
| [
{
"created": "Wed, 22 Sep 2021 18:18:26 GMT",
"version": "v1"
}
] | 2021-09-28 | [
[
"Giotis",
"Christos",
""
],
[
"Serb",
"Alexander",
""
],
[
"Manouras",
"Vasileios",
""
],
[
"Stathopoulos",
"Spyros",
""
],
[
"Prodromakis",
"Themis",
""
]
] | Biological synapses store multiple memories on top of each other in a palimpsest fashion and at different timescales. Palimpsest consolidation is facilitated by the interaction of hidden biochemical processes that govern synaptic efficacy during varying lifetimes. This arrangement allows idle memories to be temporarily overwritten without being forgotten, in favour of new memories utilised in the short-term. While embedded artificial intelligence can greatly benefit from such functionality, a practical demonstration in hardware is still missing. Here, we show how the intrinsic properties of metal-oxide volatile memristors emulate the hidden processes that support biological palimpsest consolidation. Our memristive synapses exhibit an expanded doubled capacity which can protect a consolidated long-term memory while up to hundreds of uncorrelated short-term memories temporarily overwrite it. The synapses can also implement familiarity detection of previously forgotten memories. Crucially, palimpsest operation is achieved automatically and without the need for specialised instructions. We further demonstrate a practical adaptation of this technology in the context of image vision. This showcases the use of emerging memory technologies to efficiently expand the capacity of artificial intelligence hardware towards more generalised learning memories. |
2010.08687 | Matthew Ragoza | Matthew Ragoza, Tomohide Masuda, David Ryan Koes | Learning a Continuous Representation of 3D Molecular Structures with
Deep Generative Models | Camera-ready submission to NeurIPS 2020 MLSB workshop | null | null | null | q-bio.QM cs.LG q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Machine learning in drug discovery has been focused on virtual screening of
molecular libraries using discriminative models. Generative models are an
entirely different approach that learn to represent and optimize molecules in a
continuous latent space. These methods have been increasingly successful at
generating two dimensional molecules as SMILES strings and molecular graphs. In
this work, we describe deep generative models of three dimensional molecular
structures using atomic density grids and a novel fitting algorithm for
converting continuous grids to discrete molecular structures. Our models
jointly represent drug-like molecules and their conformations in a latent space
that can be explored through interpolation. We are also able to sample diverse
sets of molecules based on a given input compound and increase the probability
of creating valid, drug-like molecules.
| [
{
"created": "Sat, 17 Oct 2020 01:15:47 GMT",
"version": "v1"
},
{
"created": "Tue, 20 Oct 2020 15:01:54 GMT",
"version": "v2"
},
{
"created": "Sun, 15 Nov 2020 03:47:25 GMT",
"version": "v3"
}
] | 2020-11-17 | [
[
"Ragoza",
"Matthew",
""
],
[
"Masuda",
"Tomohide",
""
],
[
"Koes",
"David Ryan",
""
]
] | Machine learning in drug discovery has been focused on virtual screening of molecular libraries using discriminative models. Generative models are an entirely different approach that learn to represent and optimize molecules in a continuous latent space. These methods have been increasingly successful at generating two dimensional molecules as SMILES strings and molecular graphs. In this work, we describe deep generative models of three dimensional molecular structures using atomic density grids and a novel fitting algorithm for converting continuous grids to discrete molecular structures. Our models jointly represent drug-like molecules and their conformations in a latent space that can be explored through interpolation. We are also able to sample diverse sets of molecules based on a given input compound and increase the probability of creating valid, drug-like molecules. |
1510.01403 | Radostin Simitev | Mark Christie, Manasi Nandi, Yanika Borg, Valentina Carapella, Gary
Mirams, Philip Aston, Saziye Bayram, Radostin D. Simitev, Jennifer Siggers
and Buddhapriya Chakrabarti | Mathematical Modelling of Heart Rate Changes in the Mouse | This is a report that summarises the outcomes from the UK MMSG NC3R's
Study Group meeting in London, 15th-18th April 2013 in response to a problem
entitled `Modelling heart rate changes in the mouse as a series of delayed,
weakly coupled oscillators', presented by MC and MN | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The CVS is composed of numerous interacting and dynamically regulated
physiological subsystems which each generate measurable periodic components
such that the CVS can itself be presented as a system of weakly coupled
oscillators. The interactions between these oscillators generate a chaotic
blood pressure waveform signal, where periods of apparent rhythmicity are
punctuated by asynchronous behaviour. It is this variability which seems to
characterise the normal state. We used a standard experimental data set for the
purposes of analysis and modelling. Arterial blood pressure waveform data was
collected from conscious mice instrumented with radiotelemetry devices over
$24$ hours, at a $100$ Hz and $1$ kHz time base. During a $24$ hour period,
these mice display diurnal variation leading to changes in the cardiovascular
waveform. We undertook preliminary analysis of our data using Fourier
transforms and subsequently applied a series of both linear and nonlinear
mathematical approaches in parallel. We provide a minimalistic linear and
nonlinear coupled oscillator model and employed spectral and Hilbert analysis
as well as a phase plane analysis. This provides a route to a three way
synergistic investigation of the original blood pressure data by a combination
of physiological experiments, data analysis viz. Fourier and Hilbert transforms
and attractor reconstructions, and numerical solutions of linear and nonlinear
coupled oscillator models. We believe that a minimal model of coupled
oscillator models that quantitatively describes the complex physiological data
could be developed via such a method. Further investigations of each of these
techniques will be explored in separate publications.
| [
{
"created": "Tue, 6 Oct 2015 00:28:13 GMT",
"version": "v1"
}
] | 2015-10-07 | [
[
"Christie",
"Mark",
""
],
[
"Nandi",
"Manasi",
""
],
[
"Borg",
"Yanika",
""
],
[
"Carapella",
"Valentina",
""
],
[
"Mirams",
"Gary",
""
],
[
"Aston",
"Philip",
""
],
[
"Bayram",
"Saziye",
""
],
[
"Simitev",
"Radostin D.",
""
],
[
"Siggers",
"Jennifer",
""
],
[
"Chakrabarti",
"Buddhapriya",
""
]
] | The CVS is composed of numerous interacting and dynamically regulated physiological subsystems which each generate measurable periodic components such that the CVS can itself be presented as a system of weakly coupled oscillators. The interactions between these oscillators generate a chaotic blood pressure waveform signal, where periods of apparent rhythmicity are punctuated by asynchronous behaviour. It is this variability which seems to characterise the normal state. We used a standard experimental data set for the purposes of analysis and modelling. Arterial blood pressure waveform data was collected from conscious mice instrumented with radiotelemetry devices over $24$ hours, at a $100$ Hz and $1$ kHz time base. During a $24$ hour period, these mice display diurnal variation leading to changes in the cardiovascular waveform. We undertook preliminary analysis of our data using Fourier transforms and subsequently applied a series of both linear and nonlinear mathematical approaches in parallel. We provide a minimalistic linear and nonlinear coupled oscillator model and employed spectral and Hilbert analysis as well as a phase plane analysis. This provides a route to a three way synergistic investigation of the original blood pressure data by a combination of physiological experiments, data analysis viz. Fourier and Hilbert transforms and attractor reconstructions, and numerical solutions of linear and nonlinear coupled oscillator models. We believe that a minimal model of coupled oscillator models that quantitatively describes the complex physiological data could be developed via such a method. Further investigations of each of these techniques will be explored in separate publications. |
1911.03758 | Alexandria Volkening | Alexandria Volkening, Madeline R Abbott, Dorothy Catey, Neil Chandra,
Bethany Dubois, Francesca Lim, and Bjorn Sandstede | Modeling stripe formation on growing zebrafish tailfins | null | null | null | null | q-bio.CB math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | As zebrafish develop, black and gold stripes form across their skin due to
the interactions of brightly colored pigment cells. These characteristic
patterns emerge on the growing fish body, as well as on the anal and caudal
fins. While wild-type stripes form parallel to a horizontal marker on the body,
patterns on the tailfin gradually extend distally outward. Interestingly,
several mutations lead to altered body patterns without affecting fin stripes.
Through an exploratory modeling approach, our goal is to help better understand
these differences between body and fin patterns. By adapting a prior
agent-based model of cell interactions on the fish body, we present an in
silico study of stripe development on tailfins. Our main result is a
demonstration that two cell types can produce stripes on the caudal fin. We
highlight several ways that bone rays, growth, and the body-fin interface may
be involved in patterning, and we raise questions for future work related to
pattern robustness.
| [
{
"created": "Sat, 9 Nov 2019 19:11:50 GMT",
"version": "v1"
}
] | 2019-11-12 | [
[
"Volkening",
"Alexandria",
""
],
[
"Abbott",
"Madeline R",
""
],
[
"Catey",
"Dorothy",
""
],
[
"Chandra",
"Neil",
""
],
[
"Dubois",
"Bethany",
""
],
[
"Lim",
"Francesca",
""
],
[
"Sandstede",
"Bjorn",
""
]
] | As zebrafish develop, black and gold stripes form across their skin due to the interactions of brightly colored pigment cells. These characteristic patterns emerge on the growing fish body, as well as on the anal and caudal fins. While wild-type stripes form parallel to a horizontal marker on the body, patterns on the tailfin gradually extend distally outward. Interestingly, several mutations lead to altered body patterns without affecting fin stripes. Through an exploratory modeling approach, our goal is to help better understand these differences between body and fin patterns. By adapting a prior agent-based model of cell interactions on the fish body, we present an in silico study of stripe development on tailfins. Our main result is a demonstration that two cell types can produce stripes on the caudal fin. We highlight several ways that bone rays, growth, and the body-fin interface may be involved in patterning, and we raise questions for future work related to pattern robustness. |
0812.3988 | Thierry Rabilloud | Mireille Chevallet (BBSI), Sylvie Luche (BBSI), H\'el\`ene Diemer
(IPHC), Jean-Marc Strub (IPHC), Alain Van Dorsselaer (IPHC), Thierry
Rabilloud (BBSI) | Sweet silver: A formaldehyde-free silver staining using aldoses as
developing agents, with enhanced compatibility with mass spectrometry | null | Proteomics 8, 23-24 (2008) 4853-61 | 10.1002/pmic.200800321 | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Protein detection methods after electrophoresis have to be sensitive,
homogeneous, and not to impair downstream analysis of proteins by MS. Speed,
low cost, and user friendliness are also favored features. Silver staining
combines many of these features, but its compatibility with MS is limited. We
describe here, a new variant of silver staining that is completely
formaldehyde-free. Reducing sugars in alkaline borate buffer are used as
developers. While keeping the benefits of silver staining, this method is shown
to afford a much better performance in terms of compatibility with MS, both in
PMF by MALDI and in LC/ESI/MS/MS.
| [
{
"created": "Sat, 20 Dec 2008 18:24:52 GMT",
"version": "v1"
}
] | 2008-12-23 | [
[
"Chevallet",
"Mireille",
"",
"BBSI"
],
[
"Luche",
"Sylvie",
"",
"BBSI"
],
[
"Diemer",
"Hélène",
"",
"IPHC"
],
[
"Strub",
"Jean-Marc",
"",
"IPHC"
],
[
"Van Dorsselaer",
"Alain",
"",
"IPHC"
],
[
"Rabilloud",
"Thierry",
"",
"BBSI"
]
] | Protein detection methods after electrophoresis have to be sensitive, homogeneous, and not to impair downstream analysis of proteins by MS. Speed, low cost, and user friendliness are also favored features. Silver staining combines many of these features, but its compatibility with MS is limited. We describe here, a new variant of silver staining that is completely formaldehyde-free. Reducing sugars in alkaline borate buffer are used as developers. While keeping the benefits of silver staining, this method is shown to afford a much better performance in terms of compatibility with MS, both in PMF by MALDI and in LC/ESI/MS/MS. |
2401.09513 | Nicolas Weidberg | Antonella Rivera, Nicolas Weidberg, Antonio F. Pardi\~nas, Ricardo
Gonzalez-Gil, Luc{\i}a Garc{\i}a- Florez, Jose Luis Acu\~na | Role of Upwelling on Larval Dispersal and Productivity of Gooseneck
Barnacle Populations in the Cantabrian Sea: Management Implications | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | The effect of coastal upwelling on the recruitment and connectivity of
coastal marine populations has rarely been characterized to a level of detail
to be included into sound fishery management strategies. The gooseneck barnacle
(Pollicipes pollicipes) fishery at the Cantabrian Coast (Northern Spain) is
located at the fringes of the NW Spanish Upwelling system. This fishery is
being co-managed through a fine-scale, interspersed set of protected rocks
where each rock receives a distinct level of protection. Such interspersion is
potentially beneficial, but the extent to which such spacing is consistent with
mean larval dispersal distances is as yet unknown. We have simulated the spread
of gooseneck barnacle larvae in the Central Cantabrian Coast using a
high-resolution time-series of current profiles measured at a nearshore
location. During a year of high upwelling activity (2009), theoretical
recruitment success was 94% with peak recruitment predicted 56 km west of the
emission point. However, for a year of low upwelling activity (2011)
theoretical recruitment success dropped to 15.4% and peak recruitment was
expected 13 km east of the emission point. This is consistent with a positive
correlation between catch rates and the Integrated Upwelling Index, using a
4-year lag to allow recruits to reach commercial size. Furthermore, a net
long-term westward larval transport was estimated by means of mitochondrial
cytochrome c oxidase subunit I (COI) sequences for five populations in the
Cantabrian Sea. Our results call into question the role of long distance
dispersal, driven by the mesoscale processes in the area, in gooseneck barnacle
populations and point to the prevalent role of small-scale, asymmetric
connectivity more consistent with the typical scale of the co-management
process in this fishery.
| [
{
"created": "Wed, 17 Jan 2024 15:10:41 GMT",
"version": "v1"
}
] | 2024-01-19 | [
[
"Rivera",
"Antonella",
""
],
[
"Weidberg",
"Nicolas",
""
],
[
"Pardiñas",
"Antonio F.",
""
],
[
"Gonzalez-Gil",
"Ricardo",
""
],
[
"Florez",
"Lucıa Garcıa-",
""
],
[
"Acuña",
"Jose Luis",
""
]
] | The effect of coastal upwelling on the recruitment and connectivity of coastal marine populations has rarely been characterized to a level of detail to be included into sound fishery management strategies. The gooseneck barnacle (Pollicipes pollicipes) fishery at the Cantabrian Coast (Northern Spain) is located at the fringes of the NW Spanish Upwelling system. This fishery is being co-managed through a fine-scale, interspersed set of protected rocks where each rock receives a distinct level of protection. Such interspersion is potentially beneficial, but the extent to which such spacing is consistent with mean larval dispersal distances is as yet unknown. We have simulated the spread of gooseneck barnacle larvae in the Central Cantabrian Coast using a high-resolution time-series of current profiles measured at a nearshore location. During a year of high upwelling activity (2009), theoretical recruitment success was 94% with peak recruitment predicted 56 km west of the emission point. However, for a year of low upwelling activity (2011) theoretical recruitment success dropped to 15.4% and peak recruitment was expected 13 km east of the emission point. This is consistent with a positive correlation between catch rates and the Integrated Upwelling Index, using a 4-year lag to allow recruits to reach commercial size. Furthermore, a net long-term westward larval transport was estimated by means of mitochondrial cytochrome c oxidase subunit I (COI) sequences for five populations in the Cantabrian Sea. Our results call into question the role of long distance dispersal, driven by the mesoscale processes in the area, in gooseneck barnacle populations and point to the prevalent role of small-scale, asymmetric connectivity more consistent with the typical scale of the co-management process in this fishery. |
2203.08298 | Alex Viguerie PhD | Alex Viguerie, Margherita Carletti, Alessandro Veneziani, Guido
Silvestri | Modeling of Asymptotically Periodic Outbreaks: a long-term SIRW2
description of COVID-19? | null | null | null | null | q-bio.PE math.DS | http://creativecommons.org/licenses/by/4.0/ | As the outbreak of COVID-19 enters its third year, we have now enough data to
analyse the behavior of the pandemic with mathematical models over a long
period of time. The pandemic alternates periods of high and low infections, in
a way that sheds a light on the nature of mathematical model that can be used
for reliable predictions. The main hypothesis of the model presented here is
that the oscillatory behavior is a structural feature of the outbreak, even
without postulating a time-dependence of the coefficients. As such, it should
be reflected by the presence of limit cycles as asymptotic solutions. This
stems from the introduction of (i) a non-linear waning immunity based on the
concept of immunity booster (already used for other pathologies); (ii) a fine
description of the compartments with a discrimination between individuals
infected/vaccinated for the first time, and individuals already
infected/vaccinated, undergoing to new infections/doses. We provide a
proof-of-concept that our novel model is capable of reproducing long-term
oscillatory behavior of many infectious diseases, and, in particular, the
periodic nature of the waves of infection. Periodic solutions are inherent to
the model, and achieved without changing parameter values in time. This may
represent an important step in the long-term modeling of COVID-19 and similar
diseases, as the natural, unforced behavior of the solution shows the
qualitative characteristics observed during the COVID-19 pandemic.
| [
{
"created": "Tue, 15 Mar 2022 22:27:02 GMT",
"version": "v1"
}
] | 2022-03-17 | [
[
"Viguerie",
"Alex",
""
],
[
"Carletti",
"Margherita",
""
],
[
"Veneziani",
"Alessandro",
""
],
[
"Silvestri",
"Guido",
""
]
] | As the outbreak of COVID-19 enters its third year, we have now enough data to analyse the behavior of the pandemic with mathematical models over a long period of time. The pandemic alternates periods of high and low infections, in a way that sheds a light on the nature of mathematical model that can be used for reliable predictions. The main hypothesis of the model presented here is that the oscillatory behavior is a structural feature of the outbreak, even without postulating a time-dependence of the coefficients. As such, it should be reflected by the presence of limit cycles as asymptotic solutions. This stems from the introduction of (i) a non-linear waning immunity based on the concept of immunity booster (already used for other pathologies); (ii) a fine description of the compartments with a discrimination between individuals infected/vaccinated for the first time, and individuals already infected/vaccinated, undergoing to new infections/doses. We provide a proof-of-concept that our novel model is capable of reproducing long-term oscillatory behavior of many infectious diseases, and, in particular, the periodic nature of the waves of infection. Periodic solutions are inherent to the model, and achieved without changing parameter values in time. This may represent an important step in the long-term modeling of COVID-19 and similar diseases, as the natural, unforced behavior of the solution shows the qualitative characteristics observed during the COVID-19 pandemic. |
q-bio/0510039 | Fred Thaheld H | Fred Thaheld | Biological nonlocality and the mind-brain interaction problem: comments
on a new empirical approach | 21 pages | BioSystems 70 (2003) 35-41 | null | null | q-bio.NC quant-ph | null | Up to now, we have been faced with an age old fundamental dilemma posed by
the mind-brain interaction problem, i.e. how is it that the mind which is
subjective and immaterial, can interact with the brain which is objective and
material? Analysis of recent experiments appears to indicate that quantum
mechanics may have a role to play in the resolution of the mind-brain
interaction problem in the form of biological entanglement and nonlocality.
This analysis, when coupled with ongoing and proposed experiments, may help us
to simultaneously resolve related issues such as whether mental events can
initiate neural events, the transference of conscious subjective experience,
the measurement problem and the binding problem.
| [
{
"created": "Wed, 19 Oct 2005 13:30:25 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Thaheld",
"Fred",
""
]
] | Up to now, we have been faced with an age old fundamental dilemma posed by the mind-brain interaction problem, i.e. how is it that the mind which is subjective and immaterial, can interact with the brain which is objective and material? Analysis of recent experiments appears to indicate that quantum mechanics may have a role to play in the resolution of the mind-brain interaction problem in the form of biological entanglement and nonlocality. This analysis, when coupled with ongoing and proposed experiments, may help us to simultaneously resolve related issues such as whether mental events can initiate neural events, the transference of conscious subjective experience, the measurement problem and the binding problem. |
1910.07916 | Chengran Fang | Chengran Fang, Van-Dang Nguyen, Demian Wassermann, Jing-Rebecca Li | Diffusion MRI simulation of realistic neurons with SpinDoctor and the
Neuron Module | 42 pages, 17 figures. arXiv admin note: text overlap with
arXiv:1902.01025 | null | null | null | q-bio.NC physics.bio-ph physics.med-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we present the Neuron Module that we implemented within the
Matlab-based diffusion MRI simulation toolbox SpinDoctor. SpinDoctor uses
finite element discretization and adaptive time integration to solve the
Bloch-Torrey partial differential equation for general diffusion-encoding
sequences, at multiple b-values and in multiple diffusion directions. In order
to facilitate the diffusion MRI simulation of realistic neurons by the research
community, we constructed finite element meshes for a group of 36 pyramidal
neurons and a group of 29 spindle neurons whose morphological descriptions were
found in the publicly available neuron repository NeuroMorpho. We also broke
the neurons into the soma and dendrite branches and created finite elements
meshes for these cell components. Through the Neuron Module, these neuron and
cell components finite element meshes can be seamlessly coupled with the
functionalities of SpinDoctor. To illustrate some potential uses of the Neuron
Module, we show numerical examples of the simulated diffusion MRI signals in
multiple diffusion directions from whole neurons as well as from the soma and
dendrite branches, and include a comparison of the high b-value behavior
between dendrite branches and whole neurons. In addition, we demonstrate that
the neuron meshes can be used to perform Monte-Carlo diffusion MRI simulations
as well. We show that at equivalent accuracy, if only one gradient direction
needs to be simulated, SpinDoctor is faster than a GPU implementation of
Monte-Carlo. Finally, we numerically compute the eigenfunctions and the
eigenvalues of the Bloch-Torrey and the Laplace operators on the neuron
geometries using a finite elements discretization, in order to give guidance in
the choice of the space and time discretization parameters for both finite
elements and Monte-Carlo approaches.
| [
{
"created": "Wed, 16 Oct 2019 12:41:25 GMT",
"version": "v1"
},
{
"created": "Tue, 14 Apr 2020 09:29:26 GMT",
"version": "v2"
},
{
"created": "Tue, 21 Jul 2020 07:54:03 GMT",
"version": "v3"
}
] | 2020-07-22 | [
[
"Fang",
"Chengran",
""
],
[
"Nguyen",
"Van-Dang",
""
],
[
"Wassermann",
"Demian",
""
],
[
"Li",
"Jing-Rebecca",
""
]
] | In this paper we present the Neuron Module that we implemented within the Matlab-based diffusion MRI simulation toolbox SpinDoctor. SpinDoctor uses finite element discretization and adaptive time integration to solve the Bloch-Torrey partial differential equation for general diffusion-encoding sequences, at multiple b-values and in multiple diffusion directions. In order to facilitate the diffusion MRI simulation of realistic neurons by the research community, we constructed finite element meshes for a group of 36 pyramidal neurons and a group of 29 spindle neurons whose morphological descriptions were found in the publicly available neuron repository NeuroMorpho. We also broke the neurons into the soma and dendrite branches and created finite elements meshes for these cell components. Through the Neuron Module, these neuron and cell components finite element meshes can be seamlessly coupled with the functionalities of SpinDoctor. To illustrate some potential uses of the Neuron Module, we show numerical examples of the simulated diffusion MRI signals in multiple diffusion directions from whole neurons as well as from the soma and dendrite branches, and include a comparison of the high b-value behavior between dendrite branches and whole neurons. In addition, we demonstrate that the neuron meshes can be used to perform Monte-Carlo diffusion MRI simulations as well. We show that at equivalent accuracy, if only one gradient direction needs to be simulated, SpinDoctor is faster than a GPU implementation of Monte-Carlo. Finally, we numerically compute the eigenfunctions and the eigenvalues of the Bloch-Torrey and the Laplace operators on the neuron geometries using a finite elements discretization, in order to give guidance in the choice of the space and time discretization parameters for both finite elements and Monte-Carlo approaches. |
2207.13040 | Predrag Janjic | Predrag Janjic, Dimitar Solev and Ljupco Kocarev | Non-trivial dynamics in a model of glial membrane voltage driven by open
potassium pores | null | null | 10.1016/j.bpj.2023.03.013 | null | q-bio.NC physics.bio-ph q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Despite the molecular evidence that close to linear steady state I-V
relationship in mammalian astrocytes reflects a total current resulting from
more than one differently regulated K+ conductances, detailed ODE models of
membrane voltage Vm incorporating multiple conductances are lacking. Repeated
results of deregulated expressions of major K+ channels in glia, Kir4.1, in
models of disease, as well as their altered rectification when assembling
heteromeric Kir4.1/Kir5.1 channels have motivated us to attempt a detailed
model adding the weaker potassium K2P current, in addition to Kir4.1, and study
the stability of the resting state Vr. We ask whether with a deregulated Kir
conductivity the nominal resting state Vr remains stable, and the cell retains
a potassium electrode behavior with Vm following E_K. The minimal 2-dimensional
model near Vr showed that certain alterations of Kir4.1 current may result in
multistability of Vm if the model incorporates the typically observed K+
currents: Kir, K2P, and non-specific potassium leak. More specifically, a
decrease or loss of outward Kir4.1 conductance introduces instability of Vr,
near E_K. That happens through a fold bifurcation giving birth to a much more
depolarized second, stable resting state Vdr>-10 mV. Realistic timeseries were
used to perturb the membrane model, from recordings at the glial membrane
during electrographic seizures. Simulations of the perturbed system by constant
current through GJCs and transient seizure-like discharges as local field
potentials led to depolarization of the astrocyte and switching of Vm between
the two stable states, in a down-state / up-state manner. If the prolonged
depolarizations near Vdr prove experimentally plausible, such catastrophic
instability would impact all aspects of the glial function, from metabolic
support to membrane transport and practically all neuromodulatory roles
assigned to glia.
| [
{
"created": "Tue, 26 Jul 2022 17:01:44 GMT",
"version": "v1"
},
{
"created": "Fri, 30 Sep 2022 21:45:10 GMT",
"version": "v2"
}
] | 2023-05-03 | [
[
"Janjic",
"Predrag",
""
],
[
"Solev",
"Dimitar",
""
],
[
"Kocarev",
"Ljupco",
""
]
] | Despite the molecular evidence that close to linear steady state I-V relationship in mammalian astrocytes reflects a total current resulting from more than one differently regulated K+ conductances, detailed ODE models of membrane voltage Vm incorporating multiple conductances are lacking. Repeated results of deregulated expressions of major K+ channels in glia, Kir4.1, in models of disease, as well as their altered rectification when assembling heteromeric Kir4.1/Kir5.1 channels have motivated us to attempt a detailed model adding the weaker potassium K2P current, in addition to Kir4.1, and study the stability of the resting state Vr. We ask whether with a deregulated Kir conductivity the nominal resting state Vr remains stable, and the cell retains a potassium electrode behavior with Vm following E_K. The minimal 2-dimensional model near Vr showed that certain alterations of Kir4.1 current may result in multistability of Vm if the model incorporates the typically observed K+ currents: Kir, K2P, and non-specific potassium leak. More specifically, a decrease or loss of outward Kir4.1 conductance introduces instability of Vr, near E_K. That happens through a fold bifurcation giving birth to a much more depolarized second, stable resting state Vdr>-10 mV. Realistic timeseries were used to perturb the membrane model, from recordings at the glial membrane during electrographic seizures. Simulations of the perturbed system by constant current through GJCs and transient seizure-like discharges as local field potentials led to depolarization of the astrocyte and switching of Vm between the two stable states, in a down-state / up-state manner. If the prolonged depolarizations near Vdr prove experimentally plausible, such catastrophic instability would impact all aspects of the glial function, from metabolic support to membrane transport and practically all neuromodulatory roles assigned to glia. |
2105.07416 | Sebastian Goldt | Sebastian Goldt, Florent Krzakala, Lenka Zdeborov\'a, Nicolas Brunel | Bayesian reconstruction of memories stored in neural networks from their
connectivity | Code available at https://github.com/sgoldt/reconstructing_memories | PLOS Computational Biology 19(1): e1010813 2023 | 10.1371/journal.pcbi.1010813 | null | q-bio.NC cond-mat.stat-mech stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The advent of comprehensive synaptic wiring diagrams of large neural circuits
has created the field of connectomics and given rise to a number of open
research questions. One such question is whether it is possible to reconstruct
the information stored in a recurrent network of neurons, given its synaptic
connectivity matrix. Here, we address this question by determining when solving
such an inference problem is theoretically possible in specific attractor
network models and by providing a practical algorithm to do so. The algorithm
builds on ideas from statistical physics to perform approximate Bayesian
inference and is amenable to exact analysis. We study its performance on three
different models, compare the algorithm to standard algorithms such as PCA, and
explore the limitations of reconstructing stored patterns from synaptic
connectivity.
| [
{
"created": "Sun, 16 May 2021 12:05:10 GMT",
"version": "v1"
},
{
"created": "Mon, 29 Aug 2022 15:24:02 GMT",
"version": "v2"
}
] | 2023-02-20 | [
[
"Goldt",
"Sebastian",
""
],
[
"Krzakala",
"Florent",
""
],
[
"Zdeborová",
"Lenka",
""
],
[
"Brunel",
"Nicolas",
""
]
] | The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in a recurrent network of neurons, given its synaptic connectivity matrix. Here, we address this question by determining when solving such an inference problem is theoretically possible in specific attractor network models and by providing a practical algorithm to do so. The algorithm builds on ideas from statistical physics to perform approximate Bayesian inference and is amenable to exact analysis. We study its performance on three different models, compare the algorithm to standard algorithms such as PCA, and explore the limitations of reconstructing stored patterns from synaptic connectivity. |
2002.03419 | Razvan Marinescu | Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E.
Bron, Arthur W. Toga, Michael W. Weiner, Frederik Barkhof, Nick C. Fox, Arman
Eshaghi, Tina Toni, Marcin Salaterski, Veronika Lunina, Manon Ansart, Stanley
Durrleman, Pascal Lu, Samuel Iddi, Dan Li, Wesley K. Thompson, Michael C.
Donohue, Aviv Nahon, Yarden Levy, Dan Halbersberg, Mariya Cohen, Huiling
Liao, Tengfei Li, Kaixian Yu, Hongtu Zhu, Jose G. Tamez-Pena, Aya Ismail,
Timothy Wood, Hector Corrada Bravo, Minh Nguyen, Nanbo Sun, Jiashi Feng, B.T.
Thomas Yeo, Gang Chen, Ke Qi, Shiyang Chen, Deqiang Qiu, Ionut Buciuman, Alex
Kelner, Raluca Pop, Denisa Rimocea, Mostafa M. Ghazi, Mads Nielsen, Sebastien
Ourselin, Lauge Sorensen, Vikram Venkatraghavan, Keli Liu, Christina Rabe,
Paul Manser, Steven M. Hill, James Howlett, Zhiyue Huang, Steven Kiddle, Sach
Mukherjee, Anais Rouanet, Bernd Taschler, Brian D. M. Tom, Simon R. White,
Noel Faux, Suman Sedai, Javier de Velasco Oriol, Edgar E. V. Clemente, Karol
Estrada, Leon Aksman, Andre Altmann, Cynthia M. Stonnington, Yalin Wang,
Jianfeng Wu, Vivek Devadas, Clementine Fourrier, Lars Lau Raket, Aristeidis
Sotiras, Guray Erus, Jimit Doshi, Christos Davatzikos, Jacob Vogel, Andrew
Doyle, Angela Tam, Alex Diaz-Papkovich, Emmanuel Jammeh, Igor Koval, Paul
Moore, Terry J. Lyons, John Gallacher, Jussi Tohka, Robert Ciszek, Bruno
Jedynak, Kruti Pandya, Murat Bilgel, William Engels, Joseph Cole, Polina
Golland, Stefan Klein, Daniel C. Alexander | The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE)
Challenge: Results after 1 Year Follow-up | Presents final results of the TADPOLE competition. 60 pages, 7
tables, 14 figures | Machine Learning for Biomedical Imaging (MELBA), Dec 2021 | null | null | q-bio.PE stat.AP | http://creativecommons.org/licenses/by/4.0/ | We present the findings of "The Alzheimer's Disease Prediction Of
Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of
92 algorithms from 33 international teams at predicting the future trajectory
of 219 individuals at risk of Alzheimer's disease. Challenge participants were
required to make a prediction, for each month of a 5-year future time period,
of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale
Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The
methods used by challenge participants included multivariate linear regression,
machine learning methods such as support vector machines and deep neural
networks, as well as disease progression models. No single submission was best
at predicting all three outcomes. For clinical diagnosis and ventricle volume
prediction, the best algorithms strongly outperform simple baselines in
predictive ability. However, for ADAS-Cog13 no single submitted prediction
method was significantly better than random guesswork. Two ensemble methods
based on taking the mean and median over all predictions, obtained top scores
on almost all tasks. Better than average performance at diagnosis prediction
was generally associated with the additional inclusion of features from
cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the
other hand, better performance at ventricle volume prediction was associated
with inclusion of summary statistics, such as the slope or maxima/minima of
biomarkers. TADPOLE's unique results suggest that current prediction algorithms
provide sufficient accuracy to exploit biomarkers related to clinical diagnosis
and ventricle volume, for cohort refinement in clinical trials for Alzheimer's
disease. However, results call into question the usage of cognitive test scores
for patient selection and as a primary endpoint in clinical trials.
| [
{
"created": "Sun, 9 Feb 2020 18:32:02 GMT",
"version": "v1"
},
{
"created": "Mon, 27 Dec 2021 22:13:32 GMT",
"version": "v2"
}
] | 2021-12-30 | [
[
"Marinescu",
"Razvan V.",
""
],
[
"Oxtoby",
"Neil P.",
""
],
[
"Young",
"Alexandra L.",
""
],
[
"Bron",
"Esther E.",
""
],
[
"Toga",
"Arthur W.",
""
],
[
"Weiner",
"Michael W.",
""
],
[
"Barkhof",
"Frederik",
""
],
[
"Fox",
"Nick C.",
""
],
[
"Eshaghi",
"Arman",
""
],
[
"Toni",
"Tina",
""
],
[
"Salaterski",
"Marcin",
""
],
[
"Lunina",
"Veronika",
""
],
[
"Ansart",
"Manon",
""
],
[
"Durrleman",
"Stanley",
""
],
[
"Lu",
"Pascal",
""
],
[
"Iddi",
"Samuel",
""
],
[
"Li",
"Dan",
""
],
[
"Thompson",
"Wesley K.",
""
],
[
"Donohue",
"Michael C.",
""
],
[
"Nahon",
"Aviv",
""
],
[
"Levy",
"Yarden",
""
],
[
"Halbersberg",
"Dan",
""
],
[
"Cohen",
"Mariya",
""
],
[
"Liao",
"Huiling",
""
],
[
"Li",
"Tengfei",
""
],
[
"Yu",
"Kaixian",
""
],
[
"Zhu",
"Hongtu",
""
],
[
"Tamez-Pena",
"Jose G.",
""
],
[
"Ismail",
"Aya",
""
],
[
"Wood",
"Timothy",
""
],
[
"Bravo",
"Hector Corrada",
""
],
[
"Nguyen",
"Minh",
""
],
[
"Sun",
"Nanbo",
""
],
[
"Feng",
"Jiashi",
""
],
[
"Yeo",
"B. T. Thomas",
""
],
[
"Chen",
"Gang",
""
],
[
"Qi",
"Ke",
""
],
[
"Chen",
"Shiyang",
""
],
[
"Qiu",
"Deqiang",
""
],
[
"Buciuman",
"Ionut",
""
],
[
"Kelner",
"Alex",
""
],
[
"Pop",
"Raluca",
""
],
[
"Rimocea",
"Denisa",
""
],
[
"Ghazi",
"Mostafa M.",
""
],
[
"Nielsen",
"Mads",
""
],
[
"Ourselin",
"Sebastien",
""
],
[
"Sorensen",
"Lauge",
""
],
[
"Venkatraghavan",
"Vikram",
""
],
[
"Liu",
"Keli",
""
],
[
"Rabe",
"Christina",
""
],
[
"Manser",
"Paul",
""
],
[
"Hill",
"Steven M.",
""
],
[
"Howlett",
"James",
""
],
[
"Huang",
"Zhiyue",
""
],
[
"Kiddle",
"Steven",
""
],
[
"Mukherjee",
"Sach",
""
],
[
"Rouanet",
"Anais",
""
],
[
"Taschler",
"Bernd",
""
],
[
"Tom",
"Brian D. M.",
""
],
[
"White",
"Simon R.",
""
],
[
"Faux",
"Noel",
""
],
[
"Sedai",
"Suman",
""
],
[
"Oriol",
"Javier de Velasco",
""
],
[
"Clemente",
"Edgar E. V.",
""
],
[
"Estrada",
"Karol",
""
],
[
"Aksman",
"Leon",
""
],
[
"Altmann",
"Andre",
""
],
[
"Stonnington",
"Cynthia M.",
""
],
[
"Wang",
"Yalin",
""
],
[
"Wu",
"Jianfeng",
""
],
[
"Devadas",
"Vivek",
""
],
[
"Fourrier",
"Clementine",
""
],
[
"Raket",
"Lars Lau",
""
],
[
"Sotiras",
"Aristeidis",
""
],
[
"Erus",
"Guray",
""
],
[
"Doshi",
"Jimit",
""
],
[
"Davatzikos",
"Christos",
""
],
[
"Vogel",
"Jacob",
""
],
[
"Doyle",
"Andrew",
""
],
[
"Tam",
"Angela",
""
],
[
"Diaz-Papkovich",
"Alex",
""
],
[
"Jammeh",
"Emmanuel",
""
],
[
"Koval",
"Igor",
""
],
[
"Moore",
"Paul",
""
],
[
"Lyons",
"Terry J.",
""
],
[
"Gallacher",
"John",
""
],
[
"Tohka",
"Jussi",
""
],
[
"Ciszek",
"Robert",
""
],
[
"Jedynak",
"Bruno",
""
],
[
"Pandya",
"Kruti",
""
],
[
"Bilgel",
"Murat",
""
],
[
"Engels",
"William",
""
],
[
"Cole",
"Joseph",
""
],
[
"Golland",
"Polina",
""
],
[
"Klein",
"Stefan",
""
],
[
"Alexander",
"Daniel C.",
""
]
] | We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. The methods used by challenge participants included multivariate linear regression, machine learning methods such as support vector machines and deep neural networks, as well as disease progression models. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guesswork. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as the slope or maxima/minima of biomarkers. TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease. However, results call into question the usage of cognitive test scores for patient selection and as a primary endpoint in clinical trials. |
1504.02406 | Maja | Maja Temerinac-Ott and Armaghan W. Naik and Robert F. Murphy | Deciding when to stop: Efficient stopping of active learning guided
drug-target prediction | This paper was selected for oral presentation at RECOMB 2015 and an
abstract is published in the conference proceedings | null | null | null | q-bio.QM cs.LG stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Active learning has shown to reduce the number of experiments needed to
obtain high-confidence drug-target predictions. However, in order to actually
save experiments using active learning, it is crucial to have a method to
evaluate the quality of the current prediction and decide when to stop the
experimentation process. Only by applying reliable stoping criteria to active
learning, time and costs in the experimental process can be actually saved. We
compute active learning traces on simulated drug-target matrices in order to
learn a regression model for the accuracy of the active learner. By analyzing
the performance of the regression model on simulated data, we design stopping
criteria for previously unseen experimental matrices. We demonstrate on four
previously characterized drug effect data sets that applying the stopping
criteria can result in upto 40% savings of the total experiments for highly
accurate predictions.
| [
{
"created": "Thu, 9 Apr 2015 18:10:38 GMT",
"version": "v1"
}
] | 2015-04-10 | [
[
"Temerinac-Ott",
"Maja",
""
],
[
"Naik",
"Armaghan W.",
""
],
[
"Murphy",
"Robert F.",
""
]
] | Active learning has shown to reduce the number of experiments needed to obtain high-confidence drug-target predictions. However, in order to actually save experiments using active learning, it is crucial to have a method to evaluate the quality of the current prediction and decide when to stop the experimentation process. Only by applying reliable stoping criteria to active learning, time and costs in the experimental process can be actually saved. We compute active learning traces on simulated drug-target matrices in order to learn a regression model for the accuracy of the active learner. By analyzing the performance of the regression model on simulated data, we design stopping criteria for previously unseen experimental matrices. We demonstrate on four previously characterized drug effect data sets that applying the stopping criteria can result in upto 40% savings of the total experiments for highly accurate predictions. |
1901.08103 | Gabriel Fabricius | Gabriel Fabricius (1) and Alberto Maltz (2) ((1) INIFTA, Universidad
Nacional de La Plata, La Plata, Argentina (2) Departamento de Matem\'atica,
Universidad Nacional de La Plata, La Plata, Argentina) | Exploring the threshold of epidemic spreading for a stochastic SIR model
with local and global contacts | Accepted for publication in Physica A on October 15, 2019 | null | 10.1016/j.physa.2019.123208 | null | q-bio.PE math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The spread of an epidemic process is considered in the context of a spatial
SIR stochastic model that includes a parameter $0\le p\le 1$ that assigns
weights $p$ and $1- p$ to global and local infective contacts respectively. The
model was previously studied by other authors in different contexts. In this
work we characterized the behavior of the system around the threshold for
epidemic spreading. We first used a deterministic approximation of the
stochastic model and checked the existence of a threshold value of $p$ for
exponential epidemic spread. An analytical expression, which defines a function
of the quotient $\alpha$ between the transmission and recovery rates, is
obtained to approximate this threshold. We then performed different analyses
based on intensive stochastic simulations and found that this expression is
also a good estimate for a similar threshold value of $p$ obtained in the
stochastic model. The dynamics of the average number of infected individuals
and the average size of outbreaks show a behavior across the threshold that is
well described by the deterministic approximation. The distributions of the
outbreak sizes at the threshold present common features for all the cases
considered corresponding to different values of $\alpha>1$. These features are
otherwise already known to hold for the standard stochastic SIR model at its
threshold, $\alpha=1$: (i) the probability of having an outbreak of size $n$
goes asymptotically as $n^{-3/2}$ for an infinite system, (ii) the maximal size
of an outbreak scales as $N^{2/3}$ for a finite system of size $N$.
| [
{
"created": "Wed, 23 Jan 2019 19:54:25 GMT",
"version": "v1"
},
{
"created": "Mon, 8 Apr 2019 02:43:00 GMT",
"version": "v2"
},
{
"created": "Wed, 16 Oct 2019 11:46:28 GMT",
"version": "v3"
}
] | 2020-01-29 | [
[
"Fabricius",
"Gabriel",
""
],
[
"Maltz",
"Alberto",
""
]
] | The spread of an epidemic process is considered in the context of a spatial SIR stochastic model that includes a parameter $0\le p\le 1$ that assigns weights $p$ and $1- p$ to global and local infective contacts respectively. The model was previously studied by other authors in different contexts. In this work we characterized the behavior of the system around the threshold for epidemic spreading. We first used a deterministic approximation of the stochastic model and checked the existence of a threshold value of $p$ for exponential epidemic spread. An analytical expression, which defines a function of the quotient $\alpha$ between the transmission and recovery rates, is obtained to approximate this threshold. We then performed different analyses based on intensive stochastic simulations and found that this expression is also a good estimate for a similar threshold value of $p$ obtained in the stochastic model. The dynamics of the average number of infected individuals and the average size of outbreaks show a behavior across the threshold that is well described by the deterministic approximation. The distributions of the outbreak sizes at the threshold present common features for all the cases considered corresponding to different values of $\alpha>1$. These features are otherwise already known to hold for the standard stochastic SIR model at its threshold, $\alpha=1$: (i) the probability of having an outbreak of size $n$ goes asymptotically as $n^{-3/2}$ for an infinite system, (ii) the maximal size of an outbreak scales as $N^{2/3}$ for a finite system of size $N$. |
q-bio/0405011 | Shalev Itzkovitz | Shalev Itzkovitz, Reuven Levitt, Nadav Kashtan, Ron Milo, Michael
Itzkovitz, Uri Alon | Coarse-Graining and Self-Dissimilarity of Complex Networks | 11 pages, 11 figures | Phys. Rev. E 71, 016127 (2005) | 10.1103/PhysRevE.71.016127 | null | q-bio.MN cond-mat.stat-mech | null | Can complex engineered and biological networks be coarse-grained into smaller
and more understandable versions in which each node represents an entire
pattern in the original network? To address this, we define coarse-graining
units (CGU) as connectivity patterns which can serve as the nodes of a
coarse-grained network, and present algorithms to detect them. We use this
approach to systematically reverse-engineer electronic circuits, forming
understandable high-level maps from incomprehensible transistor wiring: first,
a coarse-grained version in which each node is a gate made of several
transistors is established. Then, the coarse-grained network is itself
coarse-grained, resulting in a high-level blueprint in which each node is a
circuit-module made of multiple gates. We apply our approach also to a
mammalian protein-signaling network, to find a simplified coarse-grained
network with three main signaling channels that correspond to cross-interacting
MAP-kinase cascades. We find that both biological and electronic networks are
'self-dissimilar', with different network motifs found at each level. The
present approach can be used to simplify a wide variety of directed and
nondirected, natural and designed networks.
| [
{
"created": "Fri, 14 May 2004 20:16:07 GMT",
"version": "v1"
},
{
"created": "Mon, 18 Oct 2004 15:40:56 GMT",
"version": "v2"
}
] | 2009-11-10 | [
[
"Itzkovitz",
"Shalev",
""
],
[
"Levitt",
"Reuven",
""
],
[
"Kashtan",
"Nadav",
""
],
[
"Milo",
"Ron",
""
],
[
"Itzkovitz",
"Michael",
""
],
[
"Alon",
"Uri",
""
]
] | Can complex engineered and biological networks be coarse-grained into smaller and more understandable versions in which each node represents an entire pattern in the original network? To address this, we define coarse-graining units (CGU) as connectivity patterns which can serve as the nodes of a coarse-grained network, and present algorithms to detect them. We use this approach to systematically reverse-engineer electronic circuits, forming understandable high-level maps from incomprehensible transistor wiring: first, a coarse-grained version in which each node is a gate made of several transistors is established. Then, the coarse-grained network is itself coarse-grained, resulting in a high-level blueprint in which each node is a circuit-module made of multiple gates. We apply our approach also to a mammalian protein-signaling network, to find a simplified coarse-grained network with three main signaling channels that correspond to cross-interacting MAP-kinase cascades. We find that both biological and electronic networks are 'self-dissimilar', with different network motifs found at each level. The present approach can be used to simplify a wide variety of directed and nondirected, natural and designed networks. |
1712.09479 | Yunxiang Ge | Yunxiang Ge, Yu Pan and Weibei Dou | Analysis of BOLD fMRI Signal Preprocessing Pipeline on Different
Datasets while Reducing False Positive Rates | ICBIBE 2018 accepted | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The technology of functional Magnetic Resonance Imaging (fMRI) based on Blood
Oxygen Level Dependent (BOLD) signal has been widely used in clinical
treatments and brain function researches. The BOLD signal has to be
preprocessed before being analyzed using either functional connectivity
measurements or statistical methods. Current researches show that data
preprocessing steps may influence the results of analysis, yet there is no
consensus on preprocessing method. In this paper, an evaluation method is
proposed for analyzing the preprocessing pipeline of resting state BOLD fMRI
(rs-BOLD fMRI) data under putative task experiment designs to cast some lights
on the preprocessing stage, covering both first and second level analysis. The
choices of preprocessing parameters and steps are altered to investigate
preprocessing pipelines while observing statistical analysis results, trying to
reduce false positives as reported by Eklund et al. in their 2016 PNAS paper.
All of the experiment data are separated into 7 datasets, consisting of 220
healthy control samples and 136 patient data that are from 38 incomplete Spinal
Cord Injury (SCI) patients and 16 Cerebral Stroke (CS) patients, including
multiple scans of some patients at different time. These data were acquired
from two different MRI scanners, which may cause difference in analysis
results. The evaluation result shows that it has little effect to change
parameters in each steps of the classical preprocessing pipeline, which
consists head motion correction, normalization and smoothing. Removing time
points and the following detrend step can reduce false positives. However,
covariates regression and filtering has complicated effects on the data. Note
that for single subject analysis, false positives declined consistently after
filtering. The result of patient data and healthy controls data which are
scanned under the same machine with ...
| [
{
"created": "Wed, 27 Dec 2017 02:20:25 GMT",
"version": "v1"
}
] | 2017-12-29 | [
[
"Ge",
"Yunxiang",
""
],
[
"Pan",
"Yu",
""
],
[
"Dou",
"Weibei",
""
]
] | The technology of functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygen Level Dependent (BOLD) signal has been widely used in clinical treatments and brain function researches. The BOLD signal has to be preprocessed before being analyzed using either functional connectivity measurements or statistical methods. Current researches show that data preprocessing steps may influence the results of analysis, yet there is no consensus on preprocessing method. In this paper, an evaluation method is proposed for analyzing the preprocessing pipeline of resting state BOLD fMRI (rs-BOLD fMRI) data under putative task experiment designs to cast some lights on the preprocessing stage, covering both first and second level analysis. The choices of preprocessing parameters and steps are altered to investigate preprocessing pipelines while observing statistical analysis results, trying to reduce false positives as reported by Eklund et al. in their 2016 PNAS paper. All of the experiment data are separated into 7 datasets, consisting of 220 healthy control samples and 136 patient data that are from 38 incomplete Spinal Cord Injury (SCI) patients and 16 Cerebral Stroke (CS) patients, including multiple scans of some patients at different time. These data were acquired from two different MRI scanners, which may cause difference in analysis results. The evaluation result shows that it has little effect to change parameters in each steps of the classical preprocessing pipeline, which consists head motion correction, normalization and smoothing. Removing time points and the following detrend step can reduce false positives. However, covariates regression and filtering has complicated effects on the data. Note that for single subject analysis, false positives declined consistently after filtering. The result of patient data and healthy controls data which are scanned under the same machine with ... |
1101.0020 | Peter Waddell | Peter J. Waddell, Ariful Azad and Ishita Khan | Resampling Residuals on Phylogenetic Trees: Extended Results | 9 pages, 2 figures, 2 tables | null | null | null | q-bio.PE q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this article the results of Waddell and Azad (2009) are extended. In
particular, the geometric percentage mean standard deviation measure of the fit
of distances to a phylogenetic tree is adjusted for the number of parameters
fitted to the model. The formulae are also presented in their general form for
any weight that is a function of the distance. The cell line gene expression
data set of Ross et al. (2000) is reanalyzed. It is shown that ordinary least
squares (OLS) is a much better fit to the data than a Neighbor Joining or BME
tree. Residual resampling shows that cancer cell lines do indeed fit a tree
fairly well and that the tree does have strong internal structure. Simulations
show that least squares tree building methods, including OLS, are strong
competitors with BME type methods for fitting model data, while real world
examples often suggest the same conclusion.
| [
{
"created": "Wed, 29 Dec 2010 23:03:02 GMT",
"version": "v1"
}
] | 2011-01-04 | [
[
"Waddell",
"Peter J.",
""
],
[
"Azad",
"Ariful",
""
],
[
"Khan",
"Ishita",
""
]
] | In this article the results of Waddell and Azad (2009) are extended. In particular, the geometric percentage mean standard deviation measure of the fit of distances to a phylogenetic tree is adjusted for the number of parameters fitted to the model. The formulae are also presented in their general form for any weight that is a function of the distance. The cell line gene expression data set of Ross et al. (2000) is reanalyzed. It is shown that ordinary least squares (OLS) is a much better fit to the data than a Neighbor Joining or BME tree. Residual resampling shows that cancer cell lines do indeed fit a tree fairly well and that the tree does have strong internal structure. Simulations show that least squares tree building methods, including OLS, are strong competitors with BME type methods for fitting model data, while real world examples often suggest the same conclusion. |
2207.08622 | Giovanni Bussi | Mattia Bernetti and Giovanni Bussi | Combining simulations and experiments to investigate RNA dynamics | Submitted to journal | Curr. Opin. Struct. Biol. 78, 102503 (2023) | 10.1016/j.sbi.2022.102503 | null | q-bio.BM physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Conformational dynamics is crucial for ribonucleic acid (RNA) function.
Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small-
and wide-angle X-ray scattering, chemical probing, single-molecule F\"orster
resonance energy transfer or even thermal or mechanical denaturation
experiments probe RNA dynamics at different time and space resolutions. Their
combination with accurate atomistic molecular dynamics (MD) simulations paves
the way for quantitative and detailed studies of RNA dynamics. First,
experiments provide a quantitative validation tool for MD simulations. Second,
available data can be used to refine simulated structural ensembles to match
experiments. Finally, comparison with experiments allows for improving MD force
fields that are transferable to new systems for which data is not available.
Here we review the recent literature and provide our perspective on this field.
| [
{
"created": "Mon, 18 Jul 2022 14:12:41 GMT",
"version": "v1"
},
{
"created": "Thu, 4 Aug 2022 12:54:44 GMT",
"version": "v2"
},
{
"created": "Thu, 25 Aug 2022 09:10:50 GMT",
"version": "v3"
}
] | 2022-12-02 | [
[
"Bernetti",
"Mattia",
""
],
[
"Bussi",
"Giovanni",
""
]
] | Conformational dynamics is crucial for ribonucleic acid (RNA) function. Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small- and wide-angle X-ray scattering, chemical probing, single-molecule F\"orster resonance energy transfer or even thermal or mechanical denaturation experiments probe RNA dynamics at different time and space resolutions. Their combination with accurate atomistic molecular dynamics (MD) simulations paves the way for quantitative and detailed studies of RNA dynamics. First, experiments provide a quantitative validation tool for MD simulations. Second, available data can be used to refine simulated structural ensembles to match experiments. Finally, comparison with experiments allows for improving MD force fields that are transferable to new systems for which data is not available. Here we review the recent literature and provide our perspective on this field. |
2101.07935 | Kyle Crocker | Kyle Crocker, Joshua Johnson, Wolfgang Pfeifer, Carlos Castro, and
Ralf Bundschuh | A quantitative model for a nanoscale switch accurately predicts thermal
actuation behavior | null | null | null | null | q-bio.BM physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Manipulation of temperature can be used to actuate DNA origami nano-hinges
containing gold nanoparticles. We develop a physical model of this system that
uses partition function analysis of the interaction between the nano-hinge and
nanoparticle to predict the probability that the nano-hinge is open at a given
temperature. The model agrees well with experimental data and predicts
experimental conditions that allow the actuation temperature of the nano-hinge
to be tuned over a range of temperatures from $30$${}^{\circ}\mathrm{C}$ to
$45$${}^{\circ}\mathrm{C}$. Additionally, the model reveals surprising physical
constraints on the system. This combination of physical insight and predictive
potential is likely to inform future designs that integrate nanoparticles into
dynamic DNA origami structures. Furthermore, our modeling approach could be
expanded to consider the incorporation, stability, and actuation of other types
of functional elements or actuation mechanisms integrated into nucleic acid
devices.
| [
{
"created": "Wed, 20 Jan 2021 02:31:56 GMT",
"version": "v1"
}
] | 2021-01-21 | [
[
"Crocker",
"Kyle",
""
],
[
"Johnson",
"Joshua",
""
],
[
"Pfeifer",
"Wolfgang",
""
],
[
"Castro",
"Carlos",
""
],
[
"Bundschuh",
"Ralf",
""
]
] | Manipulation of temperature can be used to actuate DNA origami nano-hinges containing gold nanoparticles. We develop a physical model of this system that uses partition function analysis of the interaction between the nano-hinge and nanoparticle to predict the probability that the nano-hinge is open at a given temperature. The model agrees well with experimental data and predicts experimental conditions that allow the actuation temperature of the nano-hinge to be tuned over a range of temperatures from $30$${}^{\circ}\mathrm{C}$ to $45$${}^{\circ}\mathrm{C}$. Additionally, the model reveals surprising physical constraints on the system. This combination of physical insight and predictive potential is likely to inform future designs that integrate nanoparticles into dynamic DNA origami structures. Furthermore, our modeling approach could be expanded to consider the incorporation, stability, and actuation of other types of functional elements or actuation mechanisms integrated into nucleic acid devices. |
1604.04643 | Dorjsuren Battogtokh | Dorjsuren Battogtokh and John J. Tyson | Comparison of Domain Nucleation Mechanisms in a Minimal Model of Shoot
Apical Meristem | 9 pages 16 figures | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Existing mathematical models of the shoot apical meristem (SAM) explain
nucleation and confinement of a stem cell domain by Turing's mechanism,
assuming that the diffusion coefficients of the activator (WUSCHEL) and
inhibitor (CLAVATA) are significantly different. As there is no evidence for
this assumption of differential diffusivity, we recently proposed a new
mechanism based on a bistable switch model of the SAM. Here we study the
bistable-switch mechanism in detail, demonstrating that it can be understood as
localized switches of WUSHEL activity in individual cells driven by a
non-uniform field of a peptide hormone. By comparing domain formation by Turing
and bistable-switch mechanisms on a cell network, we show that the latter does
not require the assumptions needed by the former, which are not supported by
biological evidences.
| [
{
"created": "Fri, 15 Apr 2016 21:09:45 GMT",
"version": "v1"
},
{
"created": "Tue, 19 Apr 2016 03:15:51 GMT",
"version": "v2"
},
{
"created": "Wed, 6 Dec 2017 19:00:02 GMT",
"version": "v3"
}
] | 2017-12-08 | [
[
"Battogtokh",
"Dorjsuren",
""
],
[
"Tyson",
"John J.",
""
]
] | Existing mathematical models of the shoot apical meristem (SAM) explain nucleation and confinement of a stem cell domain by Turing's mechanism, assuming that the diffusion coefficients of the activator (WUSCHEL) and inhibitor (CLAVATA) are significantly different. As there is no evidence for this assumption of differential diffusivity, we recently proposed a new mechanism based on a bistable switch model of the SAM. Here we study the bistable-switch mechanism in detail, demonstrating that it can be understood as localized switches of WUSHEL activity in individual cells driven by a non-uniform field of a peptide hormone. By comparing domain formation by Turing and bistable-switch mechanisms on a cell network, we show that the latter does not require the assumptions needed by the former, which are not supported by biological evidences. |
1606.04344 | Javier Garcia | Javier O. Garcia, Justin Brooks, Scott Kerick, Tony Johnson, Tim
Mullen, and Jean M. Vettel | Estimating direction in brain-behavior interactions: Proactive and
reactive brain states in driving | In review at NeuroImage | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Conventional neuroimaging analyses have revealed the computational
specificity of localized brain regions, exploiting the power of the subtraction
technique in fMRI and event-related potential analyses in EEG. Moving beyond
this convention, many researchers have begun exploring network-based
neurodynamics and coordination between brain regions as a function of
behavioral parameters or environmental statistics; however, most approaches
average evoked activity across the experimental session to study task-dependent
networks. Here, we examined on-going oscillatory activity and use a methodology
to estimate directionality in brain-behavior interactions. After source
reconstruction, activity within specific frequency bands in a priori regions of
interest was linked to continuous behavioral measurements, and we used a
predictive filtering scheme to estimate the asymmetry between brain-to-behavior
and behavior-to-brain prediction. We applied this approach to a simulated
driving task and examine directed relationships between brain activity and
continuous driving behavior (steering or heading error). Our results indicated
that two neuro-behavioral states emerge in this naturalistic environment: a
Proactive brain state that actively plans the response to the sensory
information, and a Reactive brain state that processes incoming information and
reacts to environmental statistics.
| [
{
"created": "Tue, 14 Jun 2016 13:29:08 GMT",
"version": "v1"
}
] | 2016-06-15 | [
[
"Garcia",
"Javier O.",
""
],
[
"Brooks",
"Justin",
""
],
[
"Kerick",
"Scott",
""
],
[
"Johnson",
"Tony",
""
],
[
"Mullen",
"Tim",
""
],
[
"Vettel",
"Jean M.",
""
]
] | Conventional neuroimaging analyses have revealed the computational specificity of localized brain regions, exploiting the power of the subtraction technique in fMRI and event-related potential analyses in EEG. Moving beyond this convention, many researchers have begun exploring network-based neurodynamics and coordination between brain regions as a function of behavioral parameters or environmental statistics; however, most approaches average evoked activity across the experimental session to study task-dependent networks. Here, we examined on-going oscillatory activity and use a methodology to estimate directionality in brain-behavior interactions. After source reconstruction, activity within specific frequency bands in a priori regions of interest was linked to continuous behavioral measurements, and we used a predictive filtering scheme to estimate the asymmetry between brain-to-behavior and behavior-to-brain prediction. We applied this approach to a simulated driving task and examine directed relationships between brain activity and continuous driving behavior (steering or heading error). Our results indicated that two neuro-behavioral states emerge in this naturalistic environment: a Proactive brain state that actively plans the response to the sensory information, and a Reactive brain state that processes incoming information and reacts to environmental statistics. |
q-bio/0408026 | Dietrich Stauffer | M. Masa, S. Cebrat and D. Stauffer | Does telomere elongation in cloned organisms lead to a longer lifespan
if cancer is considered ? | 8 pages including 4 figures | null | null | null | q-bio.PE | null | ... By additionally considering a two-mutation model for carcinogenesis and
indefinite proliferation by the activation of telomerase, we demonstrate that
the risk of dying doe to cancer can outweigh the positive effect of longer
telomeres on the longevity.
| [
{
"created": "Mon, 30 Aug 2004 14:52:18 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Masa",
"M.",
""
],
[
"Cebrat",
"S.",
""
],
[
"Stauffer",
"D.",
""
]
] | ... By additionally considering a two-mutation model for carcinogenesis and indefinite proliferation by the activation of telomerase, we demonstrate that the risk of dying doe to cancer can outweigh the positive effect of longer telomeres on the longevity. |
1608.03465 | Danilo Bzdok | Danilo Bzdok and B. T. Thomas Yeo | The Future of Data Analysis in the Neurosciences | null | null | null | null | q-bio.NC stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Neuroscience is undergoing faster changes than ever before. Over 100 years
our field qualitatively described and invasively manipulated single or few
organisms to gain anatomical, physiological, and pharmacological insights. In
the last 10 years neuroscience spawned quantitative big-sample datasets on
microanatomy, synaptic connections, optogenetic brain-behavior assays, and
high-level cognition. While growing data availability and information
granularity have been amply discussed, we direct attention to a routinely
neglected question: How will the unprecedented data richness shape data
analysis practices? Statistical reasoning is becoming more central to distill
neurobiological knowledge from healthy and pathological brain recordings. We
believe that large-scale data analysis will use more models that are
non-parametric, generative, mixing frequentist and Bayesian aspects, and
grounded in different statistical inferences.
| [
{
"created": "Fri, 5 Aug 2016 20:43:21 GMT",
"version": "v1"
}
] | 2016-08-12 | [
[
"Bzdok",
"Danilo",
""
],
[
"Yeo",
"B. T. Thomas",
""
]
] | Neuroscience is undergoing faster changes than ever before. Over 100 years our field qualitatively described and invasively manipulated single or few organisms to gain anatomical, physiological, and pharmacological insights. In the last 10 years neuroscience spawned quantitative big-sample datasets on microanatomy, synaptic connections, optogenetic brain-behavior assays, and high-level cognition. While growing data availability and information granularity have been amply discussed, we direct attention to a routinely neglected question: How will the unprecedented data richness shape data analysis practices? Statistical reasoning is becoming more central to distill neurobiological knowledge from healthy and pathological brain recordings. We believe that large-scale data analysis will use more models that are non-parametric, generative, mixing frequentist and Bayesian aspects, and grounded in different statistical inferences. |
1906.08246 | Jesus Malo | J. Malo, J.J. Esteve-Taboada, M. Bertalm\'io | Cortical Divisive Normalization from Wilson-Cowan Neural Dynamics | In press at the Journal of Nonlinear Science (to appear in 2024) | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Divisive Normalization and the Wilson-Cowan equations are influential models
of neural interaction and saturation [Carandini and Heeger Nat.Rev.Neurosci.
2012; Wilson and Cowan Kybernetik 1973]. However, they have not been
analytically related yet. In this work we show that Divisive Normalization can
be obtained from the Wilson-Cowan model. Specifically, assuming that Divisive
Normalization is the steady state solution of the Wilson-Cowan differential
equation, we find that the kernel that controls neural interactions in Divisive
Normalization depends on the Wilson-Cowan kernel but also has a
signal-dependent contribution. A standard stability analysis of a Wilson-Cowan
model with the parameters obtained from our relation shows that the Divisive
Normalization solution is a stable node. This stability demonstrates the
consistency of our steady state assumption.
The proposed theory provides a physiological foundation (a relation to a
dynamical network with fixed wiring among neurons) for the functional
suggestions that have been done on the need of signal-dependent Divisive
Normalization [e.g. in Coen-Cagli et al., PLoS Comp.Biol. 2012]. Moreover, this
theory explains the modifications that had to be introduced ad-hoc in Gaussian
kernels of Divisive Normalization in [Martinez et al. Front. Neurosci. 2019] to
reproduce contrast responses. The proposed relation implies that the
Wilson-Cowan dynamics also reproduces visual masking and subjective image
distortion metrics, which up to now had been mainly explained via Divisive
Normalization. Finally, this relation allows to apply to Divisive Normalization
the methods which up to now had been developed for dynamical systems such as
Wilson-Cowan networks.
| [
{
"created": "Wed, 19 Jun 2019 17:45:41 GMT",
"version": "v1"
},
{
"created": "Mon, 5 Aug 2019 10:19:42 GMT",
"version": "v2"
},
{
"created": "Mon, 10 Oct 2022 15:52:51 GMT",
"version": "v3"
},
{
"created": "Tue, 11 Oct 2022 20:56:01 GMT",
"version": "v4"
},
{
"created": "Sat, 23 Dec 2023 22:34:58 GMT",
"version": "v5"
},
{
"created": "Thu, 28 Dec 2023 11:15:46 GMT",
"version": "v6"
}
] | 2024-01-02 | [
[
"Malo",
"J.",
""
],
[
"Esteve-Taboada",
"J. J.",
""
],
[
"Bertalmío",
"M.",
""
]
] | Divisive Normalization and the Wilson-Cowan equations are influential models of neural interaction and saturation [Carandini and Heeger Nat.Rev.Neurosci. 2012; Wilson and Cowan Kybernetik 1973]. However, they have not been analytically related yet. In this work we show that Divisive Normalization can be obtained from the Wilson-Cowan model. Specifically, assuming that Divisive Normalization is the steady state solution of the Wilson-Cowan differential equation, we find that the kernel that controls neural interactions in Divisive Normalization depends on the Wilson-Cowan kernel but also has a signal-dependent contribution. A standard stability analysis of a Wilson-Cowan model with the parameters obtained from our relation shows that the Divisive Normalization solution is a stable node. This stability demonstrates the consistency of our steady state assumption. The proposed theory provides a physiological foundation (a relation to a dynamical network with fixed wiring among neurons) for the functional suggestions that have been done on the need of signal-dependent Divisive Normalization [e.g. in Coen-Cagli et al., PLoS Comp.Biol. 2012]. Moreover, this theory explains the modifications that had to be introduced ad-hoc in Gaussian kernels of Divisive Normalization in [Martinez et al. Front. Neurosci. 2019] to reproduce contrast responses. The proposed relation implies that the Wilson-Cowan dynamics also reproduces visual masking and subjective image distortion metrics, which up to now had been mainly explained via Divisive Normalization. Finally, this relation allows to apply to Divisive Normalization the methods which up to now had been developed for dynamical systems such as Wilson-Cowan networks. |
2306.16910 | Nicole Ille | Nicole Ille, Yoshiaki Nakao, Yano Shumpei, Toshiyuki Taura, Arndt
Ebert, Harald Bornfleth, Suguru Asagi, Kanoko Kozawa, Izumi Itabashi,
Takafumi Sato, Rie Sakuraba, Rie Tsuda, Yosuke Kakisaka, Kazutaka Jin,
Nobukazu Nakasato | Ongoing EEG artifact correction using blind source separation | 16 pages, 4 figures, 3 tables | Clinical Neurophysiology 158 (2024) 149-158 | 10.1016/j.clinph.2023.12.133 | null | q-bio.QM eess.SP stat.ME | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Objective: Analysis of the electroencephalogram (EEG) for epileptic spike and
seizure detection or brain-computer interfaces can be severely hampered by the
presence of artifacts. The aim of this study is to describe and evaluate a fast
automatic algorithm for ongoing correction of artifacts in continuous EEG
recordings, which can be applied offline and online. Methods: The automatic
algorithm for ongoing correction of artifacts is based on fast blind source
separation. It uses a sliding window technique with overlapping epochs and
features in the spatial, temporal and frequency domain to detect and correct
ocular, cardiac, muscle and powerline artifacts. Results: The approach was
validated in an independent evaluation study on publicly available continuous
EEG data with 2035 marked artifacts. Validation confirmed that 88% of the
artifacts could be removed successfully (ocular: 81%, cardiac: 84%, muscle:
98%, powerline: 100%). It outperformed state-of-the-art algorithms both in
terms of artifact reduction rates and computation time. Conclusions: Fast
ongoing artifact correction successfully removed a good proportion of
artifacts, while preserving most of the EEG signals. Significance: The
presented algorithm may be useful for ongoing correction of artifacts, e.g., in
online systems for epileptic spike and seizure detection or brain-computer
interfaces.
| [
{
"created": "Thu, 29 Jun 2023 13:01:52 GMT",
"version": "v1"
}
] | 2024-04-10 | [
[
"Ille",
"Nicole",
""
],
[
"Nakao",
"Yoshiaki",
""
],
[
"Shumpei",
"Yano",
""
],
[
"Taura",
"Toshiyuki",
""
],
[
"Ebert",
"Arndt",
""
],
[
"Bornfleth",
"Harald",
""
],
[
"Asagi",
"Suguru",
""
],
[
"Kozawa",
"Kanoko",
""
],
[
"Itabashi",
"Izumi",
""
],
[
"Sato",
"Takafumi",
""
],
[
"Sakuraba",
"Rie",
""
],
[
"Tsuda",
"Rie",
""
],
[
"Kakisaka",
"Yosuke",
""
],
[
"Jin",
"Kazutaka",
""
],
[
"Nakasato",
"Nobukazu",
""
]
] | Objective: Analysis of the electroencephalogram (EEG) for epileptic spike and seizure detection or brain-computer interfaces can be severely hampered by the presence of artifacts. The aim of this study is to describe and evaluate a fast automatic algorithm for ongoing correction of artifacts in continuous EEG recordings, which can be applied offline and online. Methods: The automatic algorithm for ongoing correction of artifacts is based on fast blind source separation. It uses a sliding window technique with overlapping epochs and features in the spatial, temporal and frequency domain to detect and correct ocular, cardiac, muscle and powerline artifacts. Results: The approach was validated in an independent evaluation study on publicly available continuous EEG data with 2035 marked artifacts. Validation confirmed that 88% of the artifacts could be removed successfully (ocular: 81%, cardiac: 84%, muscle: 98%, powerline: 100%). It outperformed state-of-the-art algorithms both in terms of artifact reduction rates and computation time. Conclusions: Fast ongoing artifact correction successfully removed a good proportion of artifacts, while preserving most of the EEG signals. Significance: The presented algorithm may be useful for ongoing correction of artifacts, e.g., in online systems for epileptic spike and seizure detection or brain-computer interfaces. |
1712.06527 | Debora Marks | Adam J. Riesselman, John B. Ingraham, Debora S. Marks | Deep generative models of genetic variation capture mutation effects | null | null | null | null | q-bio.QM cond-mat.dis-nn physics.bio-ph stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The functions of proteins and RNAs are determined by a myriad of interactions
between their constituent residues, but most quantitative models of how
molecular phenotype depends on genotype must approximate this by simple
additive effects. While recent models have relaxed this constraint to also
account for pairwise interactions, these approaches do not provide a tractable
path towards modeling higher-order dependencies. Here, we show how latent
variable models with nonlinear dependencies can be applied to capture
beyond-pairwise constraints in biomolecules. We present a new probabilistic
model for sequence families, DeepSequence, that can predict the effects of
mutations across a variety of deep mutational scanning experiments
significantly better than site independent or pairwise models that are based on
the same evolutionary data. The model, learned in an unsupervised manner solely
from sequence information, is grounded with biologically motivated priors,
reveals latent organization of sequence families, and can be used to
extrapolate to new parts of sequence space
| [
{
"created": "Mon, 18 Dec 2017 17:13:08 GMT",
"version": "v1"
}
] | 2017-12-19 | [
[
"Riesselman",
"Adam J.",
""
],
[
"Ingraham",
"John B.",
""
],
[
"Marks",
"Debora S.",
""
]
] | The functions of proteins and RNAs are determined by a myriad of interactions between their constituent residues, but most quantitative models of how molecular phenotype depends on genotype must approximate this by simple additive effects. While recent models have relaxed this constraint to also account for pairwise interactions, these approaches do not provide a tractable path towards modeling higher-order dependencies. Here, we show how latent variable models with nonlinear dependencies can be applied to capture beyond-pairwise constraints in biomolecules. We present a new probabilistic model for sequence families, DeepSequence, that can predict the effects of mutations across a variety of deep mutational scanning experiments significantly better than site independent or pairwise models that are based on the same evolutionary data. The model, learned in an unsupervised manner solely from sequence information, is grounded with biologically motivated priors, reveals latent organization of sequence families, and can be used to extrapolate to new parts of sequence space |
q-bio/0406023 | Michael Fuller . D. | Michael M. Fuller, Tamara N. Romanuk, and Jurek Kolasa | Community Structure and Metacommunity Dynamics of Aquatic Invertebrates:
a Test of the Neutral Theory | 31 pages, 7 Figures, PDF | null | null | null | q-bio.PE | null | We used a metacommunity of 49 discrete communities of aquatic invertebrates
to analyze the dynamical relationship between community and metacommunity
species distributions as a test of the neutral theory of biodiversity and
biogeography. At the community scale, observed variation in species richness
and relative abundance was greater than predicted by neutral models, and
revealed important differences among species in competitive ability and
tolerance for predation. At the metacommunity scale, species with metacommunity
proportions of less than 0.01% (38% of the observed metacommunity) were
consistently more abundant than predicted by models. Our results are at
variance with the neutral theory, and suggest that the use of an identical
survival probability for all species in neutral models misrepresents
substantial aspects of community assembly. Nevertheless, building and testing
neutral models can provide valuable insights into the processes that determine
species distributions.
| [
{
"created": "Fri, 11 Jun 2004 02:59:33 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Fuller",
"Michael M.",
""
],
[
"Romanuk",
"Tamara N.",
""
],
[
"Kolasa",
"Jurek",
""
]
] | We used a metacommunity of 49 discrete communities of aquatic invertebrates to analyze the dynamical relationship between community and metacommunity species distributions as a test of the neutral theory of biodiversity and biogeography. At the community scale, observed variation in species richness and relative abundance was greater than predicted by neutral models, and revealed important differences among species in competitive ability and tolerance for predation. At the metacommunity scale, species with metacommunity proportions of less than 0.01% (38% of the observed metacommunity) were consistently more abundant than predicted by models. Our results are at variance with the neutral theory, and suggest that the use of an identical survival probability for all species in neutral models misrepresents substantial aspects of community assembly. Nevertheless, building and testing neutral models can provide valuable insights into the processes that determine species distributions. |
1509.02341 | Caterina La Porta AM | Zsolt Bertalan, Zoe Budrikis, Caterina A. M. La Porta, Stefano Zapperi | Navigation strategies of motor proteins on decorated tracks | null | PLoS ONE 10(8): e0136945, (2015) | 10.1371/journal.pone.0136945 | null | q-bio.SC cond-mat.soft physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Motor proteins display widely different stepping patterns as they move on
microtubule tracks, from the deterministic linear or helical motion performed
by the protein kinesin to the uncoordinated random steps made by dynein. How
these different strategies produce an efficient navigation system needed to
ensure correct cellular functioning is still unclear. Here, we show by
numerical simulations that deterministic and random motor steps yield different
outcomes when random obstacles decorate the microtubule tracks: kinesin moves
faster on clean tracks but its motion is strongly hindered on decorated tracks,
while dynein is slower on clean tracks but more efficient in avoiding
obstacles. Further simulations indicate that dynein's advantage on decorated
tracks is due to its ability to step backwards. Our results explain how
different navigation strategies are employed by the cell to optimize motor
driven cargo transport.
| [
{
"created": "Tue, 8 Sep 2015 12:30:29 GMT",
"version": "v1"
}
] | 2015-09-09 | [
[
"Bertalan",
"Zsolt",
""
],
[
"Budrikis",
"Zoe",
""
],
[
"La Porta",
"Caterina A. M.",
""
],
[
"Zapperi",
"Stefano",
""
]
] | Motor proteins display widely different stepping patterns as they move on microtubule tracks, from the deterministic linear or helical motion performed by the protein kinesin to the uncoordinated random steps made by dynein. How these different strategies produce an efficient navigation system needed to ensure correct cellular functioning is still unclear. Here, we show by numerical simulations that deterministic and random motor steps yield different outcomes when random obstacles decorate the microtubule tracks: kinesin moves faster on clean tracks but its motion is strongly hindered on decorated tracks, while dynein is slower on clean tracks but more efficient in avoiding obstacles. Further simulations indicate that dynein's advantage on decorated tracks is due to its ability to step backwards. Our results explain how different navigation strategies are employed by the cell to optimize motor driven cargo transport. |
0810.4364 | Max Souza | Max O. Souza, Jorge P. Zubelli | Global stability for a class of virus models with CTL immune response
and antigenic variation | 15 pages | Bull. Math. Biol., 73, 609--625 (2011) | 10.1007/s11538-010-9543-2 | null | q-bio.PE math.CA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the global stability of a class of models for in-vivo virus
dynamics, that take into account the CTL immune response and display antigenic
variation. This class includes a number of models that have been extensively
used to model HIV dynamics. We show that models in this class are globally
asymptotically stable, under mild hypothesis, by using appropriate Lyapunov
functions. We also characterise the stable equilibrium points for the entire
biologically relevant parameter range. As a byproduct, we are able to determine
what is the diversity of the persistent strains.
| [
{
"created": "Fri, 24 Oct 2008 00:47:53 GMT",
"version": "v1"
},
{
"created": "Mon, 17 Aug 2009 01:20:52 GMT",
"version": "v2"
}
] | 2013-01-21 | [
[
"Souza",
"Max O.",
""
],
[
"Zubelli",
"Jorge P.",
""
]
] | We study the global stability of a class of models for in-vivo virus dynamics, that take into account the CTL immune response and display antigenic variation. This class includes a number of models that have been extensively used to model HIV dynamics. We show that models in this class are globally asymptotically stable, under mild hypothesis, by using appropriate Lyapunov functions. We also characterise the stable equilibrium points for the entire biologically relevant parameter range. As a byproduct, we are able to determine what is the diversity of the persistent strains. |
q-bio/0507002 | Silvia Scarpetta | Silvia Scarpetta, Maria Marinaro | A learning rule for place fields in a cortical model: theta phase
precession as a network effect | 10 pages, 7 figures, to be published in Hippocampus | null | null | null | q-bio.NC cond-mat.dis-nn | null | We show that a model of the hippocampus introduced recently by Scarpetta,
Zhaoping & Hertz ([2002] Neural Computation 14(10):2371-96), explains the theta
phase precession phenomena. In our model, the theta phase precession comes out
as a consequence of the associative-memory-like network dynamics, i.e. the
network's ability to imprint and recall oscillatory patterns, coded both by
phases and amplitudes of oscillation. The learning rule used to imprint the
oscillatory states is a natural generalization of that used for static patterns
in the Hopfield model, and is based on the spike time dependent synaptic
plasticity (STDP), experimentally observed. In agreement with experimental
findings, the place cell's activity appears at consistently earlier phases of
subsequent cycles of the ongoing theta rhythm during a pass through the place
field, while the oscillation amplitude of the place cell's firing rate
increases as the animal approaches the center of the place field and decreases
as the animal leaves the center. The total phase precession of the place cell
is lower than 360 degrees, in agreement with experiments. As the animal enters
a receptive field the place cell's activity comes slightly less than 180
degrees after the phase of maximal pyramidal cell population activity, in
agreement with the findings of Skaggs et al (1996). Our model predicts that the
theta phase is much better correlated with location than with time spent in the
receptive field. Finally, in agreement with the recent experimental findings of
Zugaro et al (2005), our model predicts that theta phase precession persists
after transient intra-hippocampal perturbation.
| [
{
"created": "Fri, 1 Jul 2005 08:30:08 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Scarpetta",
"Silvia",
""
],
[
"Marinaro",
"Maria",
""
]
] | We show that a model of the hippocampus introduced recently by Scarpetta, Zhaoping & Hertz ([2002] Neural Computation 14(10):2371-96), explains the theta phase precession phenomena. In our model, the theta phase precession comes out as a consequence of the associative-memory-like network dynamics, i.e. the network's ability to imprint and recall oscillatory patterns, coded both by phases and amplitudes of oscillation. The learning rule used to imprint the oscillatory states is a natural generalization of that used for static patterns in the Hopfield model, and is based on the spike time dependent synaptic plasticity (STDP), experimentally observed. In agreement with experimental findings, the place cell's activity appears at consistently earlier phases of subsequent cycles of the ongoing theta rhythm during a pass through the place field, while the oscillation amplitude of the place cell's firing rate increases as the animal approaches the center of the place field and decreases as the animal leaves the center. The total phase precession of the place cell is lower than 360 degrees, in agreement with experiments. As the animal enters a receptive field the place cell's activity comes slightly less than 180 degrees after the phase of maximal pyramidal cell population activity, in agreement with the findings of Skaggs et al (1996). Our model predicts that the theta phase is much better correlated with location than with time spent in the receptive field. Finally, in agreement with the recent experimental findings of Zugaro et al (2005), our model predicts that theta phase precession persists after transient intra-hippocampal perturbation. |
1204.0608 | Tobias Galla | Andrew J. Black, Arne Traulsen, Tobias Galla | Mixing times in evolutionary game dynamics | 5 pages, 3 figures | null | 10.1103/PhysRevLett.109.028101 | null | q-bio.PE cond-mat.stat-mech physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Without mutation and migration, evolutionary dynamics ultimately leads to the
extinction of all but one species. Such fixation processes are well understood
and can be characterized analytically with methods from statistical physics.
However, many biological arguments focus on stationary distributions in a
mutation-selection equilibrium. Here, we address the equilibration time
required to reach stationarity in the presence of mutation, this is known as
the mixing time in the theory of Markov processes. We show that mixing times in
evolutionary games have the opposite behaviour from fixation times when the
intensity of selection increases: In coordination games with bistabilities, the
fixation time decreases, but the mixing time increases. In coexistence games
with metastable states, the fixation time increases, but the mixing time
decreases. Our results are based on simulations and the WKB approximation of
the master equation.
| [
{
"created": "Tue, 3 Apr 2012 07:04:54 GMT",
"version": "v1"
}
] | 2015-06-04 | [
[
"Black",
"Andrew J.",
""
],
[
"Traulsen",
"Arne",
""
],
[
"Galla",
"Tobias",
""
]
] | Without mutation and migration, evolutionary dynamics ultimately leads to the extinction of all but one species. Such fixation processes are well understood and can be characterized analytically with methods from statistical physics. However, many biological arguments focus on stationary distributions in a mutation-selection equilibrium. Here, we address the equilibration time required to reach stationarity in the presence of mutation, this is known as the mixing time in the theory of Markov processes. We show that mixing times in evolutionary games have the opposite behaviour from fixation times when the intensity of selection increases: In coordination games with bistabilities, the fixation time decreases, but the mixing time increases. In coexistence games with metastable states, the fixation time increases, but the mixing time decreases. Our results are based on simulations and the WKB approximation of the master equation. |
1503.08261 | Jinzhi Lei JL | Yuanhong Bi, Zhuoqin Yang, Changjing Zhuge, Jinzhi Lei | Bifurcation analysis and potential landscape of the p53-Mdm2 oscillator
regulated by the co-activator PDCD5 | 11 pages, 8 figures | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Dynamics of p53 is known to play important roles in the regulation of cell
fate decisions in response to various stresses, and PDCD5 functions as a
co-activator of p53 to modulate the p53 dynamics. In the present paper, we
investigate how p53 dynamics are modulated by PDCD5 during the DNA damage
response using methods of bifurcation analysis and potential landscape. Our
results reveal that p53 activities can display rich dynamics under different
PDCD5 levels, including monostability, bistability with two stable steady
states, oscillations, and co-existence of a stable steady state and an
oscillatory state. Physical properties of the p53 oscillations are further
shown by the potential landscape, in which the potential force attracts the
system state to the limit cycle attractor, and the curl flux force drives the
coherent oscillation along the cyclic. We also investigate the effect of PDCD5
efficiency on inducing the p53 oscillations. We show that Hopf bifurcation is
induced by increasing the PDCD5 efficiency, and the system dynamics show clear
transition features in both barrier height and energy dissipation when the
efficiency is close to the bifurcation point. This study provides a global
picture of how PDCD5 regulates p53 dynamics via the interaction with the
p53-Mdm2 oscillator and can be helpful in understanding the complicate p53
dynamics in a more complete p53 pathway.
| [
{
"created": "Sat, 28 Mar 2015 02:47:10 GMT",
"version": "v1"
}
] | 2015-03-31 | [
[
"Bi",
"Yuanhong",
""
],
[
"Yang",
"Zhuoqin",
""
],
[
"Zhuge",
"Changjing",
""
],
[
"Lei",
"Jinzhi",
""
]
] | Dynamics of p53 is known to play important roles in the regulation of cell fate decisions in response to various stresses, and PDCD5 functions as a co-activator of p53 to modulate the p53 dynamics. In the present paper, we investigate how p53 dynamics are modulated by PDCD5 during the DNA damage response using methods of bifurcation analysis and potential landscape. Our results reveal that p53 activities can display rich dynamics under different PDCD5 levels, including monostability, bistability with two stable steady states, oscillations, and co-existence of a stable steady state and an oscillatory state. Physical properties of the p53 oscillations are further shown by the potential landscape, in which the potential force attracts the system state to the limit cycle attractor, and the curl flux force drives the coherent oscillation along the cyclic. We also investigate the effect of PDCD5 efficiency on inducing the p53 oscillations. We show that Hopf bifurcation is induced by increasing the PDCD5 efficiency, and the system dynamics show clear transition features in both barrier height and energy dissipation when the efficiency is close to the bifurcation point. This study provides a global picture of how PDCD5 regulates p53 dynamics via the interaction with the p53-Mdm2 oscillator and can be helpful in understanding the complicate p53 dynamics in a more complete p53 pathway. |
1708.00294 | Megan Owen | Daniel G. Brown and Megan Owen | Mean and Variance of Phylogenetic Trees | 26 pages, 12 figures; revisions include new dataset, improved
exposition | null | null | null | q-bio.PE math.ST stat.TH | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We describe the use of the Frechet mean and variance in the
Billera-Holmes-Vogtmann (BHV) treespace to summarize and explore the diversity
of a set of phylogenetic trees. We show that the Frechet mean is comparable to
other summary methods, and, despite its stickiness property, is more likely to
be binary than the majority-rules consensus tree. We show that the Frechet
variance is faster and more precise than commonly used variance measures. The
Frechet mean and variance are more theoretically justified, and more robust,
than previous estimates of this type, and can be estimated reasonably
efficiently, providing a foundation for building more advanced statistical
methods and leading to applications such as mean hypothesis testing.
| [
{
"created": "Tue, 1 Aug 2017 12:59:02 GMT",
"version": "v1"
},
{
"created": "Thu, 10 May 2018 20:28:04 GMT",
"version": "v2"
}
] | 2018-05-14 | [
[
"Brown",
"Daniel G.",
""
],
[
"Owen",
"Megan",
""
]
] | We describe the use of the Frechet mean and variance in the Billera-Holmes-Vogtmann (BHV) treespace to summarize and explore the diversity of a set of phylogenetic trees. We show that the Frechet mean is comparable to other summary methods, and, despite its stickiness property, is more likely to be binary than the majority-rules consensus tree. We show that the Frechet variance is faster and more precise than commonly used variance measures. The Frechet mean and variance are more theoretically justified, and more robust, than previous estimates of this type, and can be estimated reasonably efficiently, providing a foundation for building more advanced statistical methods and leading to applications such as mean hypothesis testing. |
1610.04116 | J. C. Phillips | J. C. Phillips | Quantitative Molecular Scaling Theory of Protein Amino Acid Sequences,
Structure, and Functionality | 53 pages, 16 figures | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Here we review the development of protein scaling theory, starting from
backgrounds in mathematics and statistical mechanics, and leading to biomedical
applications. Evolution has organized each protein family in different ways,
but scaling theory is both simple and effective in providing readily
transferable dynamical insights complementary for many proteins represented in
the 90 thousand static structures contained in the online Protein Data Base
(PDB). Scaling theory is a simplifying magic wand that enables one to search
the hundreds of millions of protein articles in the Web of Science, and
identify those proteins that present new cost-effective methods for early
detection and/or treatment of disease through individual protein sequences
(personalized medicine). Critical point theory is general, and recently it has
proved to be the most effective way of describing protein networks that have
evolved towards nearly perfect functionality in given environments
(self-organized criticality). Evolutionary patterns are governed by common
scaling principles, which can be quantified using scales that have been
developed bioinformatically by studying thousands of PDB structures. The most
effective scales involve either hydropathic globular sculpting interactions
averaged over length scales centered on membrane dimensions, or exposed beta
strand propensities associated with aggregative (strong) protein-protein
interactions.
| [
{
"created": "Thu, 13 Oct 2016 15:07:12 GMT",
"version": "v1"
}
] | 2016-10-14 | [
[
"Phillips",
"J. C.",
""
]
] | Here we review the development of protein scaling theory, starting from backgrounds in mathematics and statistical mechanics, and leading to biomedical applications. Evolution has organized each protein family in different ways, but scaling theory is both simple and effective in providing readily transferable dynamical insights complementary for many proteins represented in the 90 thousand static structures contained in the online Protein Data Base (PDB). Scaling theory is a simplifying magic wand that enables one to search the hundreds of millions of protein articles in the Web of Science, and identify those proteins that present new cost-effective methods for early detection and/or treatment of disease through individual protein sequences (personalized medicine). Critical point theory is general, and recently it has proved to be the most effective way of describing protein networks that have evolved towards nearly perfect functionality in given environments (self-organized criticality). Evolutionary patterns are governed by common scaling principles, which can be quantified using scales that have been developed bioinformatically by studying thousands of PDB structures. The most effective scales involve either hydropathic globular sculpting interactions averaged over length scales centered on membrane dimensions, or exposed beta strand propensities associated with aggregative (strong) protein-protein interactions. |
1404.4891 | Steven Frank | Steven A. Frank | Generative models versus underlying symmetries to explain biological
pattern | null | Journal of Evolutionary Biology 27:1172-1178 (2014) | 10.1111/jeb.12388 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mathematical models play an increasingly important role in the interpretation
of biological experiments. Studies often present a model that generates the
observations, connecting hypothesized process to an observed pattern. Such
generative models confirm the plausibility of an explanation and make testable
hypotheses for further experiments. However, studies rarely consider the broad
family of alternative models that match the same observed pattern. The
symmetries that define the broad class of matching models are in fact the only
aspects of information truly revealed by observed pattern. Commonly observed
patterns derive from simple underlying symmetries. This article illustrates the
problem by showing the symmetry associated with the observed rate of increase
in fitness in a constant environment. That underlying symmetry reveals how each
particular generative model defines a single example within the broad class of
matching models. Further progress on the relation between pattern and process
requires deeper consideration of the underlying symmetries.
| [
{
"created": "Fri, 18 Apr 2014 21:32:57 GMT",
"version": "v1"
}
] | 2014-06-18 | [
[
"Frank",
"Steven A.",
""
]
] | Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative models confirm the plausibility of an explanation and make testable hypotheses for further experiments. However, studies rarely consider the broad family of alternative models that match the same observed pattern. The symmetries that define the broad class of matching models are in fact the only aspects of information truly revealed by observed pattern. Commonly observed patterns derive from simple underlying symmetries. This article illustrates the problem by showing the symmetry associated with the observed rate of increase in fitness in a constant environment. That underlying symmetry reveals how each particular generative model defines a single example within the broad class of matching models. Further progress on the relation between pattern and process requires deeper consideration of the underlying symmetries. |
1608.05706 | Joel Zylberberg | Joel Zylberberg, Alexandre Pouget, Peter E. Latham, and Eric
Shea-Brown | Robust information propagation through noisy neural circuits | null | PLoS Computational Biology 13: e1005497 (2017) | 10.1371/journal.pcbi.1005497 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sensory neurons give highly variable responses to stimulation, which can
limit the amount of stimulus information available to downstream circuits. Much
work has investigated the factors that affect the amount of information encoded
in these population responses, leading to insights about the role of
covariability among neurons, tuning curve shape, etc. However, the
informativeness of neural responses is not the only relevant feature of
population codes; of potentially equal importance is how robustly that
information propagates to downstream structures. For instance, to quantify the
retina's performance, one must consider not only the informativeness of the
optic nerve responses, but also the amount of information that survives the
spike-generating nonlinearity and noise corruption in the next stage of
processing, the lateral geniculate nucleus. Our study identifies the set of
covariance structures for the upstream cells that optimize the ability of
information to propagate through noisy, nonlinear circuits. Within this optimal
family are covariances with "differential correlations", which are known to
reduce the information encoded in neural population activities. Thus,
covariance structures that maximize information in neural population codes, and
those that maximize the ability of this information to propagate, can be very
different.
| [
{
"created": "Fri, 19 Aug 2016 19:52:11 GMT",
"version": "v1"
},
{
"created": "Sun, 26 Feb 2017 15:41:09 GMT",
"version": "v2"
}
] | 2017-04-20 | [
[
"Zylberberg",
"Joel",
""
],
[
"Pouget",
"Alexandre",
""
],
[
"Latham",
"Peter E.",
""
],
[
"Shea-Brown",
"Eric",
""
]
] | Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in these population responses, leading to insights about the role of covariability among neurons, tuning curve shape, etc. However, the informativeness of neural responses is not the only relevant feature of population codes; of potentially equal importance is how robustly that information propagates to downstream structures. For instance, to quantify the retina's performance, one must consider not only the informativeness of the optic nerve responses, but also the amount of information that survives the spike-generating nonlinearity and noise corruption in the next stage of processing, the lateral geniculate nucleus. Our study identifies the set of covariance structures for the upstream cells that optimize the ability of information to propagate through noisy, nonlinear circuits. Within this optimal family are covariances with "differential correlations", which are known to reduce the information encoded in neural population activities. Thus, covariance structures that maximize information in neural population codes, and those that maximize the ability of this information to propagate, can be very different. |
q-bio/0401002 | Carsten Peterson | Stuart Kauffman, Carsten Peterson, Bj\"orn Samuelsson, Carl Troein | Random Boolean Network Models and the Yeast Transcriptional Network | 23 pages, 5 figures | Proc. Natl. Acad. Sci. USA 100 (2003) 14796-14799 | 10.1073/pnas.2036429100 | null | q-bio.MN cond-mat.soft | null | The recently measured yeast transcriptional network is analyzed in terms of
simplified Boolean network models, with the aim of determining feasible rule
structures, given the requirement of stable solutions of the generated Boolean
networks. We find that for ensembles of generated models, those with canalyzing
Boolean rules are remarkably stable, whereas those with random Boolean rules
are only marginally stable. Furthermore, substantial parts of the generated
networks are frozen, in the sense that they reach the same state regardless of
initial state. Thus, our ensemble approach suggests that the yeast network
shows highly ordered dynamics.
| [
{
"created": "Sat, 3 Jan 2004 11:07:40 GMT",
"version": "v1"
}
] | 2009-11-10 | [
[
"Kauffman",
"Stuart",
""
],
[
"Peterson",
"Carsten",
""
],
[
"Samuelsson",
"Björn",
""
],
[
"Troein",
"Carl",
""
]
] | The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense that they reach the same state regardless of initial state. Thus, our ensemble approach suggests that the yeast network shows highly ordered dynamics. |
q-bio/0604032 | Tobias Munk | Tobias Munk, Oskar Hallatschek, Chris H. Wiggins and Erwin Frey | Dynamics of Semiflexible Polymers in a Flow Field | Corrected Label in Fig. 2. 12 pages, 10 figures | Physical Review E, Vol. 74, No. 4, 041911 (2006) | 10.1103/PhysRevE.74.041911 | LMU-ASC 25/06 | q-bio.BM cond-mat.soft | null | We present a novel method to investigate the dynamics of a single
semiflexible polymer, subject to anisotropic friction in a viscous fluid. In
contrast to previous approaches, we do not rely on a discrete bead-rod model,
but introduce a suitable normal mode decomposition of a continuous space curve.
By means of a perturbation expansion for stiff filaments we derive a closed set
of coupled Langevin equations in mode space for the nonlinear dynamics in two
dimensions, taking into account exactly the local constraint of
inextensibility. The stochastic differential equations obtained this way are
solved numerically, with parameters adjusted to describe the motion of actin
filaments. As an example, we show results for the tumbling motion in shear
flow.
| [
{
"created": "Wed, 26 Apr 2006 11:56:44 GMT",
"version": "v1"
},
{
"created": "Thu, 27 Apr 2006 17:13:56 GMT",
"version": "v2"
},
{
"created": "Thu, 7 Sep 2006 12:51:49 GMT",
"version": "v3"
},
{
"created": "Wed, 18 Oct 2006 08:45:38 GMT",
"version": "v4"
}
] | 2009-11-13 | [
[
"Munk",
"Tobias",
""
],
[
"Hallatschek",
"Oskar",
""
],
[
"Wiggins",
"Chris H.",
""
],
[
"Frey",
"Erwin",
""
]
] | We present a novel method to investigate the dynamics of a single semiflexible polymer, subject to anisotropic friction in a viscous fluid. In contrast to previous approaches, we do not rely on a discrete bead-rod model, but introduce a suitable normal mode decomposition of a continuous space curve. By means of a perturbation expansion for stiff filaments we derive a closed set of coupled Langevin equations in mode space for the nonlinear dynamics in two dimensions, taking into account exactly the local constraint of inextensibility. The stochastic differential equations obtained this way are solved numerically, with parameters adjusted to describe the motion of actin filaments. As an example, we show results for the tumbling motion in shear flow. |
1107.3111 | Alberto Bernacchia Ph.D. | Alberto Bernacchia and Xiao-Jing Wang | Decorrelation by recurrent inhibition in heterogeneous neural circuits | 31 pages, 10 figures | null | null | null | q-bio.NC math-ph math.MP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The activity of neurons is correlated, and this correlation affects how the
brain processes information. We study the neural circuit mechanisms of
correlations by analyzing a network model characterized by strong and
heterogeneous interactions: excitatory input drives the fluctuations of neural
activity, which are counterbalanced by inhibitory feedback. In particular,
excitatory input tends to correlate neurons, while inhibitory feedback reduces
correlations. We demonstrate that heterogeneity of synaptic connections is
necessary for this inhibition of correlations. We calculate statistical
averages over the disordered synaptic interactions, and we apply our findings
to both a simple linear model and to a more realistic spiking network model. We
find that correlations at zero time-lag are positive and of magnitude K^{-1/2},
where K is the number of connections to a neuron. Correlations at longer
timescales are of smaller magnitude, of order K^{-1}, implying that inhibition
of correlations occurs quickly, on a timescale of K^{-1/2}. The small magnitude
of correlations agrees qualitatively with physiological measurements in the
Cerebral Cortex and Basal Ganglia. The model could be used to study
correlations in brain regions dominated by recurrent inhibition, such as the
Striatum and Globus Pallidus.
| [
{
"created": "Fri, 15 Jul 2011 17:20:20 GMT",
"version": "v1"
},
{
"created": "Fri, 19 Aug 2011 15:28:41 GMT",
"version": "v2"
},
{
"created": "Tue, 15 Nov 2011 22:07:02 GMT",
"version": "v3"
},
{
"created": "Fri, 30 Nov 2012 20:55:08 GMT",
"version": "v4"
}
] | 2012-12-03 | [
[
"Bernacchia",
"Alberto",
""
],
[
"Wang",
"Xiao-Jing",
""
]
] | The activity of neurons is correlated, and this correlation affects how the brain processes information. We study the neural circuit mechanisms of correlations by analyzing a network model characterized by strong and heterogeneous interactions: excitatory input drives the fluctuations of neural activity, which are counterbalanced by inhibitory feedback. In particular, excitatory input tends to correlate neurons, while inhibitory feedback reduces correlations. We demonstrate that heterogeneity of synaptic connections is necessary for this inhibition of correlations. We calculate statistical averages over the disordered synaptic interactions, and we apply our findings to both a simple linear model and to a more realistic spiking network model. We find that correlations at zero time-lag are positive and of magnitude K^{-1/2}, where K is the number of connections to a neuron. Correlations at longer timescales are of smaller magnitude, of order K^{-1}, implying that inhibition of correlations occurs quickly, on a timescale of K^{-1/2}. The small magnitude of correlations agrees qualitatively with physiological measurements in the Cerebral Cortex and Basal Ganglia. The model could be used to study correlations in brain regions dominated by recurrent inhibition, such as the Striatum and Globus Pallidus. |
1605.02186 | Keita Kamino | Keita Kamino and Yohei Kondo | Rescaling of spatio-temporal sensing in eukaryotic chemotaxis | null | null | 10.1371/journal.pone.0164674 | null | q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Eukaryotic cells respond to a chemoattractant gradient by forming
intracellular gradients of signaling molecules that reflect the extracellular
chemical gradient - an ability called directional sensing. Quantitative
experiments have revealed two characteristic input-output relations of the
system: First, in a static chemoattractant gradient, the shapes of the
intracellular gradients of the signaling molecules are determined by the
relative steepness, rather than the absolute concentration, of the
chemoattractant gradient along the cell body. Second, upon a spatially
homogeneous temporal increase in the input stimulus, the intracellular
signaling molecules are transiently activated such that the response magnitudes
are dependent on fold changes of the stimulus, not on absolute levels. However,
the underlying mechanism that endows the system with these response properties
remains elusive. Here, by adopting a widely used modeling framework of
directional sensing, local excitation and global inhibition (LEGI), we propose
a hypothesis that the two rescaling behaviors stem from a single design
principle, namely, invariance of the governing equations to a scale
transformation of the input level. Analyses of the LEGI-based model reveal that
the invariance can be divided into two parts, each of which is responsible for
the respective response properties. Our hypothesis leads to an experimentally
testable prediction that a system with the invariance detects relative
steepness even in dynamic gradient stimuli as well as in static gradients.
Furthermore, we show that the relation between the response properties and the
scale invariance is general in that it can be implemented by models with
different network topologies.
| [
{
"created": "Sat, 7 May 2016 12:36:49 GMT",
"version": "v1"
},
{
"created": "Tue, 25 Oct 2016 15:53:01 GMT",
"version": "v2"
}
] | 2017-02-08 | [
[
"Kamino",
"Keita",
""
],
[
"Kondo",
"Yohei",
""
]
] | Eukaryotic cells respond to a chemoattractant gradient by forming intracellular gradients of signaling molecules that reflect the extracellular chemical gradient - an ability called directional sensing. Quantitative experiments have revealed two characteristic input-output relations of the system: First, in a static chemoattractant gradient, the shapes of the intracellular gradients of the signaling molecules are determined by the relative steepness, rather than the absolute concentration, of the chemoattractant gradient along the cell body. Second, upon a spatially homogeneous temporal increase in the input stimulus, the intracellular signaling molecules are transiently activated such that the response magnitudes are dependent on fold changes of the stimulus, not on absolute levels. However, the underlying mechanism that endows the system with these response properties remains elusive. Here, by adopting a widely used modeling framework of directional sensing, local excitation and global inhibition (LEGI), we propose a hypothesis that the two rescaling behaviors stem from a single design principle, namely, invariance of the governing equations to a scale transformation of the input level. Analyses of the LEGI-based model reveal that the invariance can be divided into two parts, each of which is responsible for the respective response properties. Our hypothesis leads to an experimentally testable prediction that a system with the invariance detects relative steepness even in dynamic gradient stimuli as well as in static gradients. Furthermore, we show that the relation between the response properties and the scale invariance is general in that it can be implemented by models with different network topologies. |
1111.2608 | Konstantin Klemm | Stephanie Keller-Schmidt and Konstantin Klemm | A model of macro-evolution as a branching process based on innovations | 16 pages, 8 figures, 1 table, v2: minor corrections and additions | Advances in Complex Systems 15, 1250043 (2012) | 10.1142/S0219525912500439 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We introduce a model for the evolution of species triggered by generation of
novel features and exhaustive combination with other available traits. Under
the assumption that innovations are rare, we obtain a bursty branching process
of speciations. Analysis of the trees representing the branching history
reveals structures qualitatively different from those of random processes. For
a tree with n leaves, the average distance of leaves from root scales as (log
n)^2 to be compared to log n for random branching. The mean values and standard
deviations for the tree shape indices depth (Sackin index) and imbalance
(Colless index) of the model are compatible with those of real phylogenetic
trees from databases. Earlier models, such as the Aldous' branching (AB) model,
show a larger deviation from data with respect to the shape indices.
| [
{
"created": "Thu, 10 Nov 2011 21:00:10 GMT",
"version": "v1"
},
{
"created": "Tue, 22 Nov 2011 08:38:16 GMT",
"version": "v2"
}
] | 2014-01-29 | [
[
"Keller-Schmidt",
"Stephanie",
""
],
[
"Klemm",
"Konstantin",
""
]
] | We introduce a model for the evolution of species triggered by generation of novel features and exhaustive combination with other available traits. Under the assumption that innovations are rare, we obtain a bursty branching process of speciations. Analysis of the trees representing the branching history reveals structures qualitatively different from those of random processes. For a tree with n leaves, the average distance of leaves from root scales as (log n)^2 to be compared to log n for random branching. The mean values and standard deviations for the tree shape indices depth (Sackin index) and imbalance (Colless index) of the model are compatible with those of real phylogenetic trees from databases. Earlier models, such as the Aldous' branching (AB) model, show a larger deviation from data with respect to the shape indices. |
1902.01978 | David Albers | DJ Albers, M Levine, L Mamykina and G Hripcsak | The Parameter Houlihan: a solution to high-throughput identifiability
indeterminacy for brutally ill-posed problems | null | null | null | null | q-bio.QM stat.ME | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | One way to interject knowledge into clinically impactful forecasting is to
use data assimilation, a nonlinear regression that projects data onto a
mechanistic physiologic model, instead of a set of functions, such as neural
networks. Such regressions have an advantage of being useful with particularly
sparse, non-stationary clinical data. However, physiological models are often
nonlinear and can have many parameters, leading to potential problems with
parameter identifiability, or the ability to find a unique set of parameters
that minimize forecasting error. The identifiability problems can be minimized
or eliminated by reducing the number of parameters estimated, but reducing the
number of estimated parameters also reduces the flexibility of the model and
hence increases forecasting error. We propose a method, the parameter Houlihan,
that combines traditional machine learning techniques with data assimilation,
to select the right set of model parameters to minimize forecasting error while
reducing identifiability problems. The method worked well: the data
assimilation-based glucose forecasts and estimates for our cohort using the
Houlihan-selected parameter sets generally also minimize forecasting errors
compared to other parameter selection methods such as by-hand parameter
selection. Nevertheless, the forecast with the lowest forecast error does not
always accurately represent physiology, but further advancements of the
algorithm provide a path for improving physiologic fidelity as well. Our hope
is that this methodology represents a first step toward combining machine
learning with data assimilation and provides a lower-threshold entry point for
using data assimilation with clinical data by helping select the right
parameters to estimate.
| [
{
"created": "Tue, 5 Feb 2019 23:42:25 GMT",
"version": "v1"
}
] | 2019-02-07 | [
[
"Albers",
"DJ",
""
],
[
"Levine",
"M",
""
],
[
"Mamykina",
"L",
""
],
[
"Hripcsak",
"G",
""
]
] | One way to interject knowledge into clinically impactful forecasting is to use data assimilation, a nonlinear regression that projects data onto a mechanistic physiologic model, instead of a set of functions, such as neural networks. Such regressions have an advantage of being useful with particularly sparse, non-stationary clinical data. However, physiological models are often nonlinear and can have many parameters, leading to potential problems with parameter identifiability, or the ability to find a unique set of parameters that minimize forecasting error. The identifiability problems can be minimized or eliminated by reducing the number of parameters estimated, but reducing the number of estimated parameters also reduces the flexibility of the model and hence increases forecasting error. We propose a method, the parameter Houlihan, that combines traditional machine learning techniques with data assimilation, to select the right set of model parameters to minimize forecasting error while reducing identifiability problems. The method worked well: the data assimilation-based glucose forecasts and estimates for our cohort using the Houlihan-selected parameter sets generally also minimize forecasting errors compared to other parameter selection methods such as by-hand parameter selection. Nevertheless, the forecast with the lowest forecast error does not always accurately represent physiology, but further advancements of the algorithm provide a path for improving physiologic fidelity as well. Our hope is that this methodology represents a first step toward combining machine learning with data assimilation and provides a lower-threshold entry point for using data assimilation with clinical data by helping select the right parameters to estimate. |
1511.03472 | Michael Idowu | Michael A. Idowu | Instantaneous Modelling and Reverse Engineering of DataConsistent Prime
Models in Seconds! | Complex Adaptive Systems San Jose, CA November 2-4, 2015, 11 figures,
8 pages | Idowu, MA. Procedia Computer Science, Complex Adaptive Systems San
Jose, CA, 61, 373-380, 2015 | 10.1016/j.procs.2015.09.163 | null | q-bio.QM nlin.AO stat.ML | http://creativecommons.org/licenses/by-nc-sa/4.0/ | A theoretical framework that supports automated construction of dynamic prime
models purely from experimental time series data has been invented and
developed, which can automatically generate (construct) data-driven models of
any time series data in seconds. This has resulted in the formulation and
formalisation of new reverse engineering and dynamic methods for automated
systems modelling of complex systems, including complex biological, financial,
control, and artificial neural network systems. The systems/model theory behind
the invention has been formalised as a new, effective and robust system
identification strategy complementary to process-based modelling. The proposed
dynamic modelling and network inference solutions often involve tackling
extremely difficult parameter estimation challenges, inferring unknown
underlying network structures, and unsupervised formulation and construction of
smart and intelligent ODE models of complex systems. In underdetermined
conditions, i.e., cases of dealing with how best to instantaneously and rapidly
construct data-consistent prime models of unknown (or well-studied) complex
system from small-sized time series data, inference of unknown underlying
network of interaction is more challenging. This article reports a robust
step-by-step mathematical and computational analysis of the entire prime model
construction process that determines a model from data in less than a minute.
| [
{
"created": "Wed, 11 Nov 2015 12:18:58 GMT",
"version": "v1"
}
] | 2015-11-12 | [
[
"Idowu",
"Michael A.",
""
]
] | A theoretical framework that supports automated construction of dynamic prime models purely from experimental time series data has been invented and developed, which can automatically generate (construct) data-driven models of any time series data in seconds. This has resulted in the formulation and formalisation of new reverse engineering and dynamic methods for automated systems modelling of complex systems, including complex biological, financial, control, and artificial neural network systems. The systems/model theory behind the invention has been formalised as a new, effective and robust system identification strategy complementary to process-based modelling. The proposed dynamic modelling and network inference solutions often involve tackling extremely difficult parameter estimation challenges, inferring unknown underlying network structures, and unsupervised formulation and construction of smart and intelligent ODE models of complex systems. In underdetermined conditions, i.e., cases of dealing with how best to instantaneously and rapidly construct data-consistent prime models of unknown (or well-studied) complex system from small-sized time series data, inference of unknown underlying network of interaction is more challenging. This article reports a robust step-by-step mathematical and computational analysis of the entire prime model construction process that determines a model from data in less than a minute. |
1602.08299 | Haiping Huang | Haiping Huang | Theory of population coupling and applications to describe high order
correlations in large populations of interacting neurons | 14 pages, 8 figures, Journal of Statistical Mechanics: Theory and
Experiment (in press) | J. Stat. Mech. (2017) 033501 | 10.1088/1742-5468/aa5dc8 | null | q-bio.NC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | To understand the collective spiking activity in neuronal populations, it is
essential to reveal basic circuit variables responsible for these emergent
functional states. Here, I develop a mean field theory for the population
coupling recently proposed in the studies of visual cortex of mouse and monkey,
relating the individual neuron activity to the population activity, and extend
the original form to the second order, relating neuron-pair's activity to the
population activity, to explain the high order correlations observed in the
neural data. I test the computational framework on the salamander retinal data
and the cortical spiking data of behaving rats. For the retinal data, the
original form of population coupling and its advanced form can explain a
significant fraction of two-cell correlations and three-cell correlations,
respectively. For the cortical data, the performance becomes much better, and
the second order population coupling reveals non-local effects in local
cortical circuits.
| [
{
"created": "Fri, 26 Feb 2016 12:50:58 GMT",
"version": "v1"
},
{
"created": "Tue, 21 Jun 2016 08:38:30 GMT",
"version": "v2"
},
{
"created": "Wed, 1 Feb 2017 01:21:09 GMT",
"version": "v3"
}
] | 2017-03-06 | [
[
"Huang",
"Haiping",
""
]
] | To understand the collective spiking activity in neuronal populations, it is essential to reveal basic circuit variables responsible for these emergent functional states. Here, I develop a mean field theory for the population coupling recently proposed in the studies of visual cortex of mouse and monkey, relating the individual neuron activity to the population activity, and extend the original form to the second order, relating neuron-pair's activity to the population activity, to explain the high order correlations observed in the neural data. I test the computational framework on the salamander retinal data and the cortical spiking data of behaving rats. For the retinal data, the original form of population coupling and its advanced form can explain a significant fraction of two-cell correlations and three-cell correlations, respectively. For the cortical data, the performance becomes much better, and the second order population coupling reveals non-local effects in local cortical circuits. |
1704.08848 | John Helliwell R | John R Helliwell | Data science skills for referees: I Biological X-ray crystallography | null | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Since there is now a growing wish by referees to judge the underpinning data
for a submitted article it is timely to provide a summary of the data
evaluation checks required to be done by a referee. As these checks will vary
from field to field this article focuses on the needs of biological X-ray
crystallography articles, which is the predominantly used method leading to
depositions in the PDB. The expected referee checks of data underpinning an
article are described with examples. These checks necessarily include that a
referee checks the PDB validation report for each crystal structure
accompanying the article submission; this check whilst necessary is not
sufficient for a complete evaluation. A referee would be expected to undertake
one cycle of model refinement of the authors biological macromolecule
coordinates against the authors processed diffraction data and look at the
various validation checks of the model and Fo-Fc electron density maps in e.g.
Phenix_refine and in COOT. If the referee deems necessary the diffraction data
images should be reprocessed (e.g. to a different diffraction resolution than
the authors submission). This can be requested to be done by the authors or if
the referee prefers can be undertaken directly by the referee themselves. A
referee wishing to do these data checks may wish to receive a certificate that
they have command of these data science skills. The organisation of such
voluntary certification training can e.g. be via those crystallography
associations duly recognised by the IUCr to issue such certificates.
| [
{
"created": "Fri, 28 Apr 2017 08:47:29 GMT",
"version": "v1"
}
] | 2017-05-01 | [
[
"Helliwell",
"John R",
""
]
] | Since there is now a growing wish by referees to judge the underpinning data for a submitted article it is timely to provide a summary of the data evaluation checks required to be done by a referee. As these checks will vary from field to field this article focuses on the needs of biological X-ray crystallography articles, which is the predominantly used method leading to depositions in the PDB. The expected referee checks of data underpinning an article are described with examples. These checks necessarily include that a referee checks the PDB validation report for each crystal structure accompanying the article submission; this check whilst necessary is not sufficient for a complete evaluation. A referee would be expected to undertake one cycle of model refinement of the authors biological macromolecule coordinates against the authors processed diffraction data and look at the various validation checks of the model and Fo-Fc electron density maps in e.g. Phenix_refine and in COOT. If the referee deems necessary the diffraction data images should be reprocessed (e.g. to a different diffraction resolution than the authors submission). This can be requested to be done by the authors or if the referee prefers can be undertaken directly by the referee themselves. A referee wishing to do these data checks may wish to receive a certificate that they have command of these data science skills. The organisation of such voluntary certification training can e.g. be via those crystallography associations duly recognised by the IUCr to issue such certificates. |
2302.07509 | Navin Cooray | Navin Cooray, Zhenglin Li, Jinzhuo Wang, Christine Lo, Mahnaz Arvaneh,
Mkael Symmonds, Michele Hu, Maarten De Vos, Lyudmila S Mihaylova | Automated Movement Detection with Dirichlet Process Mixture Models and
Electromyography | null | 2022 25th International Conference on Information Fusion (FUSION),
Link\"oping, Sweden, 2022, pp. 01-08 | 10.23919/FUSION49751.2022.9841235 | null | q-bio.QM eess.SP | http://creativecommons.org/licenses/by/4.0/ | Numerous sleep disorders are characterised by movement during sleep, these
include rapid-eye movement sleep behaviour disorder (RBD) and periodic limb
movement disorder. The process of diagnosing movement related sleep disorders
requires laborious and time-consuming visual analysis of sleep recordings. This
process involves sleep clinicians visually inspecting electromyogram (EMG)
signals to identify abnormal movements. The distribution of characteristics
that represent movement can be diverse and varied, ranging from brief moments
of tensing to violent outbursts. This study proposes a framework for automated
limb-movement detection by fusing data from two EMG sensors (from the left and
right limb) through a Dirichlet process mixture model. Several features are
extracted from 10 second mini-epochs, where each mini-epoch has been classified
as 'leg-movement' or 'no leg-movement' based on annotations of movement from
sleep clinicians. The distributions of the features from each category can be
estimated accurately using Gaussian mixture models with the Dirichlet process
as a prior. The available dataset includes 36 participants that have all been
diagnosed with RBD. The performance of this framework was evaluated by a
10-fold cross validation scheme (participant independent). The study was
compared to a random forest model and outperformed it with a mean accuracy,
sensitivity, and specificity of 94\%, 48\%, and 95\%, respectively. These
results demonstrate the ability of this framework to automate the detection of
limb movement for the potential application of assisting clinical diagnosis and
decision-making.
| [
{
"created": "Wed, 15 Feb 2023 08:00:28 GMT",
"version": "v1"
}
] | 2023-02-16 | [
[
"Cooray",
"Navin",
""
],
[
"Li",
"Zhenglin",
""
],
[
"Wang",
"Jinzhuo",
""
],
[
"Lo",
"Christine",
""
],
[
"Arvaneh",
"Mahnaz",
""
],
[
"Symmonds",
"Mkael",
""
],
[
"Hu",
"Michele",
""
],
[
"De Vos",
"Maarten",
""
],
[
"Mihaylova",
"Lyudmila S",
""
]
] | Numerous sleep disorders are characterised by movement during sleep, these include rapid-eye movement sleep behaviour disorder (RBD) and periodic limb movement disorder. The process of diagnosing movement related sleep disorders requires laborious and time-consuming visual analysis of sleep recordings. This process involves sleep clinicians visually inspecting electromyogram (EMG) signals to identify abnormal movements. The distribution of characteristics that represent movement can be diverse and varied, ranging from brief moments of tensing to violent outbursts. This study proposes a framework for automated limb-movement detection by fusing data from two EMG sensors (from the left and right limb) through a Dirichlet process mixture model. Several features are extracted from 10 second mini-epochs, where each mini-epoch has been classified as 'leg-movement' or 'no leg-movement' based on annotations of movement from sleep clinicians. The distributions of the features from each category can be estimated accurately using Gaussian mixture models with the Dirichlet process as a prior. The available dataset includes 36 participants that have all been diagnosed with RBD. The performance of this framework was evaluated by a 10-fold cross validation scheme (participant independent). The study was compared to a random forest model and outperformed it with a mean accuracy, sensitivity, and specificity of 94\%, 48\%, and 95\%, respectively. These results demonstrate the ability of this framework to automate the detection of limb movement for the potential application of assisting clinical diagnosis and decision-making. |
1910.10559 | Roman Pogodin | Roman Pogodin, Dane Corneil, Alexander Seeholzer, Joseph Heng, Wulfram
Gerstner | Working memory facilitates reward-modulated Hebbian learning in
recurrent neural networks | NeurIPS 2019 workshop "Real Neurons & Hidden Units: Future directions
at the intersection of neuroscience and artificial intelligence", Vancouver,
Canada | null | null | null | q-bio.NC cs.NE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Reservoir computing is a powerful tool to explain how the brain learns
temporal sequences, such as movements, but existing learning schemes are either
biologically implausible or too inefficient to explain animal performance. We
show that a network can learn complicated sequences with a reward-modulated
Hebbian learning rule if the network of reservoir neurons is combined with a
second network that serves as a dynamic working memory and provides a
spatio-temporal backbone signal to the reservoir. In combination with the
working memory, reward-modulated Hebbian learning of the readout neurons
performs as well as FORCE learning, but with the advantage of a biologically
plausible interpretation of both the learning rule and the learning paradigm.
| [
{
"created": "Wed, 23 Oct 2019 13:42:53 GMT",
"version": "v1"
}
] | 2019-10-24 | [
[
"Pogodin",
"Roman",
""
],
[
"Corneil",
"Dane",
""
],
[
"Seeholzer",
"Alexander",
""
],
[
"Heng",
"Joseph",
""
],
[
"Gerstner",
"Wulfram",
""
]
] | Reservoir computing is a powerful tool to explain how the brain learns temporal sequences, such as movements, but existing learning schemes are either biologically implausible or too inefficient to explain animal performance. We show that a network can learn complicated sequences with a reward-modulated Hebbian learning rule if the network of reservoir neurons is combined with a second network that serves as a dynamic working memory and provides a spatio-temporal backbone signal to the reservoir. In combination with the working memory, reward-modulated Hebbian learning of the readout neurons performs as well as FORCE learning, but with the advantage of a biologically plausible interpretation of both the learning rule and the learning paradigm. |
1808.10752 | Simone Cassani | Simone Cassani and Sarah D. Olson | A hybrid cellular automaton model of cartilage regeneration capturing
the interactions between cellular dynamics and scaffold porosity | 32 pages, 15 figures. Submitted to Journal of Mathematical Biology,
under review | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | To accelerate the development of strategies for cartilage tissue engineering,
models are necessary to study the interactions between cellular dynamics and
scaffold (SC) porosity. In experiments, cells are seeded in a porous SC where
over a month, the SC slowly degrades while cells divide and synthesize
extracellular matrix (ECM) constituents. We use an off-lattice cellular
automaton framework to model the individual behavior of cells within the SC.
The movement of cells and the ability to reproduce is determined by the
nutrient profile and local porosity. A phenomenological approach is used to
capture a continuous profile for SC and ECM evolution, which will then change
the local porosity. We parameterize the model by matching total cell counts to
chondrocytes seeded in a polyglycolic acid SC. We investigate the total cell
count and location of various cell populations for different initial SC
porosities. Similar to experiments, we observe cell counts that level off
around day 15 with higher values in SCs of lower initial porosity. Cell
clustering is observed in regions at the edge of the construct that are close
to the nutrient-rich medium in the fluid bath. Model results show that a bias
in motion due to sensitivity to porosity allows cells to move in a more optimal
arrangement. We investigate the distribution of cells as the cell reproduction
rate, cell movement distance, and sensitivity to porosity is varied. We observe
non monotonic changes in total cell counts within different regions of the
construct due to the interplay between porosity and cellular movement. We also
analyze the emergent average cell speed for different initial SC porosities,
observing an higher average for the lowest initial SC porosity. This model
provides a framework to further investigate how changes in biological
parameters can change the cellular count and distribution in SCs of different
initial porosity
| [
{
"created": "Wed, 29 Aug 2018 18:02:43 GMT",
"version": "v1"
}
] | 2018-09-03 | [
[
"Cassani",
"Simone",
""
],
[
"Olson",
"Sarah D.",
""
]
] | To accelerate the development of strategies for cartilage tissue engineering, models are necessary to study the interactions between cellular dynamics and scaffold (SC) porosity. In experiments, cells are seeded in a porous SC where over a month, the SC slowly degrades while cells divide and synthesize extracellular matrix (ECM) constituents. We use an off-lattice cellular automaton framework to model the individual behavior of cells within the SC. The movement of cells and the ability to reproduce is determined by the nutrient profile and local porosity. A phenomenological approach is used to capture a continuous profile for SC and ECM evolution, which will then change the local porosity. We parameterize the model by matching total cell counts to chondrocytes seeded in a polyglycolic acid SC. We investigate the total cell count and location of various cell populations for different initial SC porosities. Similar to experiments, we observe cell counts that level off around day 15 with higher values in SCs of lower initial porosity. Cell clustering is observed in regions at the edge of the construct that are close to the nutrient-rich medium in the fluid bath. Model results show that a bias in motion due to sensitivity to porosity allows cells to move in a more optimal arrangement. We investigate the distribution of cells as the cell reproduction rate, cell movement distance, and sensitivity to porosity is varied. We observe non monotonic changes in total cell counts within different regions of the construct due to the interplay between porosity and cellular movement. We also analyze the emergent average cell speed for different initial SC porosities, observing an higher average for the lowest initial SC porosity. This model provides a framework to further investigate how changes in biological parameters can change the cellular count and distribution in SCs of different initial porosity |
1604.03676 | Sona John | Kavita Jain and Sona John | Deterministic evolution of an asexual population under the action of
beneficial and deleterious mutations on additive fitness landscapes | To appear in Theoretical Population Biology | Theo. Pop. Biol. 112, 117-125 (2016) | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study a continuous time model for the frequency distribution of an
infinitely large asexual population in which both beneficial and deleterious
mutations occur and the fitness is additive. When beneficial mutations are
ignored, the exact solution for the frequency distribution is known to be a
Poisson distribution. Here we include beneficial mutations and obtain exact
expressions for the frequency distribution at all times using an eigenfunction
expansion method. We find that the stationary distribution is non-Poissonian
and related to the Bessel function of the first kind. We also provide suitable
approximations for the stationary distribution and the time to relax to the
steady state. Our exact results, especially at mutation-selection equilibrium,
can be useful in developing semi-deterministic approaches to understand
stochastic evolution.
| [
{
"created": "Wed, 13 Apr 2016 07:10:31 GMT",
"version": "v1"
},
{
"created": "Wed, 31 Aug 2016 12:49:15 GMT",
"version": "v2"
}
] | 2016-10-27 | [
[
"Jain",
"Kavita",
""
],
[
"John",
"Sona",
""
]
] | We study a continuous time model for the frequency distribution of an infinitely large asexual population in which both beneficial and deleterious mutations occur and the fitness is additive. When beneficial mutations are ignored, the exact solution for the frequency distribution is known to be a Poisson distribution. Here we include beneficial mutations and obtain exact expressions for the frequency distribution at all times using an eigenfunction expansion method. We find that the stationary distribution is non-Poissonian and related to the Bessel function of the first kind. We also provide suitable approximations for the stationary distribution and the time to relax to the steady state. Our exact results, especially at mutation-selection equilibrium, can be useful in developing semi-deterministic approaches to understand stochastic evolution. |
1808.00210 | Christele Etchegaray | Christ\`ele Etchegaray (IMT), Nicolas Meunier (MAP5 - UMR 8145) | Crawling migration under chemical signalling: a stochastic particle
model | null | null | 10.1002/mma.5145 | null | q-bio.CB math.PR | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cell migration is a fundamental process involved in physiological phenomena
such as the immune response and morphogenesis, but also in pathological
processes, such as the development of tumor metastasis. These functions are
effectively ensured because cells are active systems that adapt to their
environment. In this work, we consider a migrating cell as an active particle,
where its intracellular activity is responsible for motion. Such system was
already modeled in a previous model where the protrusion activity of the cell
was described by a stochastic Markovian jump process. The model was proven able
to capture the diversity in observed trajectories. Here, we add a description
of the effect of an external chemical attractive signal on the protrusion
dynamics, that may vary in time. We show that the resulting stochastic model is
a well-posed non-homogeneous Markovian process, and provide cell trajectories
in different settings, illustrating the effects of the signal on long-term
trajectories.
| [
{
"created": "Wed, 1 Aug 2018 07:51:44 GMT",
"version": "v1"
}
] | 2018-12-26 | [
[
"Etchegaray",
"Christèle",
"",
"IMT"
],
[
"Meunier",
"Nicolas",
"",
"MAP5 - UMR 8145"
]
] | Cell migration is a fundamental process involved in physiological phenomena such as the immune response and morphogenesis, but also in pathological processes, such as the development of tumor metastasis. These functions are effectively ensured because cells are active systems that adapt to their environment. In this work, we consider a migrating cell as an active particle, where its intracellular activity is responsible for motion. Such system was already modeled in a previous model where the protrusion activity of the cell was described by a stochastic Markovian jump process. The model was proven able to capture the diversity in observed trajectories. Here, we add a description of the effect of an external chemical attractive signal on the protrusion dynamics, that may vary in time. We show that the resulting stochastic model is a well-posed non-homogeneous Markovian process, and provide cell trajectories in different settings, illustrating the effects of the signal on long-term trajectories. |
2111.07445 | Lam Ho | Lam Si Tung Ho and Vu Dinh | When can we reconstruct the ancestral state? A unified theory | null | null | null | null | q-bio.PE math.ST stat.TH | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Ancestral state reconstruction is one of the most important tasks in
evolutionary biology. Conditions under which we can reliably reconstruct the
ancestral state have been studied for both discrete and continuous traits.
However, the connection between these results is unclear, and it seems that
each model needs different conditions. In this work, we provide a unifying
theory on the consistency of ancestral state reconstruction for various types
of trait evolution models. Notably, we show that for a sequence of nested trees
with bounded heights, the necessary and sufficient conditions for the existence
of a consistent ancestral state reconstruction method under discrete models,
the Brownian motion model, and the threshold model are equivalent. When tree
heights are unbounded, we provide a simple counter-example to show that this
equivalence is no longer valid.
| [
{
"created": "Sun, 14 Nov 2021 20:50:47 GMT",
"version": "v1"
}
] | 2021-11-16 | [
[
"Ho",
"Lam Si Tung",
""
],
[
"Dinh",
"Vu",
""
]
] | Ancestral state reconstruction is one of the most important tasks in evolutionary biology. Conditions under which we can reliably reconstruct the ancestral state have been studied for both discrete and continuous traits. However, the connection between these results is unclear, and it seems that each model needs different conditions. In this work, we provide a unifying theory on the consistency of ancestral state reconstruction for various types of trait evolution models. Notably, we show that for a sequence of nested trees with bounded heights, the necessary and sufficient conditions for the existence of a consistent ancestral state reconstruction method under discrete models, the Brownian motion model, and the threshold model are equivalent. When tree heights are unbounded, we provide a simple counter-example to show that this equivalence is no longer valid. |
1212.4583 | Christos Skiadas H | Christos H. Skiadas and Charilaos Skiadas | A Method for Estimating the Total Loss of Healthy Life Years:
Applications and Comparisons in UK and Scotland | 15 pages, 8 figures, 4 tables | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We propose a method of estimating the Total Loss of Healthy Life Years based
on the first exit time theory for a stochastic process, the resulting Health
State Function and the Deterioration Function estimated as the curvature of the
health state function. We have done many applications in UK and Scotland and
Sweden supporting our theory. Furthermore it was proven that both the WHO and
EU estimates of the healthy life expectancy can result from our method. The WHO
system takes into account the severe and moderate causes in estimating the loss
of healthy life years; instead the EU system calculates the total loss of
healthy life years. For both cases our methodology provides both estimators
from only death and population data. The advantages of our method are
straightforward. We do not need survey data to make the calculations. The
resulting estimates should be used to test and improve the existing survey
based methodologies. While the WHO and EU systems tend to approach each other
differences continue to appear based on the methodology of the related surveys
and the analysis of data. Two main schools are working to these directions one
based on USA the Institute for Health Metrics and Evaluation (IHME) headed by
Christopher J.L. Murray and contributors in all over the world and the European
Health and Life Expectancy Information System (EHLEIS) with Jean-Marie Robine
and a team from the EU member states. Keywords: Deterioration, Loss of healthy
years, HALE, DALE, World Health Organization, WHO, European Union, EU, EHEMU,
IHME, EHLEIS, Healthy life expectancy, Life expectancy.
| [
{
"created": "Wed, 19 Dec 2012 06:34:06 GMT",
"version": "v1"
}
] | 2012-12-20 | [
[
"Skiadas",
"Christos H.",
""
],
[
"Skiadas",
"Charilaos",
""
]
] | We propose a method of estimating the Total Loss of Healthy Life Years based on the first exit time theory for a stochastic process, the resulting Health State Function and the Deterioration Function estimated as the curvature of the health state function. We have done many applications in UK and Scotland and Sweden supporting our theory. Furthermore it was proven that both the WHO and EU estimates of the healthy life expectancy can result from our method. The WHO system takes into account the severe and moderate causes in estimating the loss of healthy life years; instead the EU system calculates the total loss of healthy life years. For both cases our methodology provides both estimators from only death and population data. The advantages of our method are straightforward. We do not need survey data to make the calculations. The resulting estimates should be used to test and improve the existing survey based methodologies. While the WHO and EU systems tend to approach each other differences continue to appear based on the methodology of the related surveys and the analysis of data. Two main schools are working to these directions one based on USA the Institute for Health Metrics and Evaluation (IHME) headed by Christopher J.L. Murray and contributors in all over the world and the European Health and Life Expectancy Information System (EHLEIS) with Jean-Marie Robine and a team from the EU member states. Keywords: Deterioration, Loss of healthy years, HALE, DALE, World Health Organization, WHO, European Union, EU, EHEMU, IHME, EHLEIS, Healthy life expectancy, Life expectancy. |
1506.04226 | Tomasz Rutkowski | Tomasz M. Rutkowski | Student Teaching and Research Laboratory Focusing on Brain-computer
Interface Paradigms - A Creative Environment for Computer Science Students - | 4 pages, 4 figures, accepted for EMBC 2015, IEEE copyright | null | 10.1109/EMBC.2015.7319188 | null | q-bio.NC cs.HC cs.RO | http://creativecommons.org/licenses/by-nc-sa/3.0/ | This paper presents an applied concept of a brain-computer interface (BCI)
student research laboratory (BCI-LAB) at the Life Science Center of TARA,
University of Tsukuba, Japan. Several successful case studies of the student
projects are reviewed together with the BCI Research Award 2014 winner case.
The BCI-LAB design and project-based teaching philosophy is also explained.
Future teaching and research directions summarize the review.
| [
{
"created": "Sat, 13 Jun 2015 05:15:33 GMT",
"version": "v1"
}
] | 2016-11-17 | [
[
"Rutkowski",
"Tomasz M.",
""
]
] | This paper presents an applied concept of a brain-computer interface (BCI) student research laboratory (BCI-LAB) at the Life Science Center of TARA, University of Tsukuba, Japan. Several successful case studies of the student projects are reviewed together with the BCI Research Award 2014 winner case. The BCI-LAB design and project-based teaching philosophy is also explained. Future teaching and research directions summarize the review. |
1304.2613 | Neill Lambert | Guang-Yin Chen and Neill Lambert and Che-Ming Li and Yueh-Nan Chen and
Franco Nori | Rerouting Excitation Transfer in the Fenna-Matthews-Olson Complex | null | Phys. Rev. E 88, 032120 (2013) | 10.1103/PhysRevE.88.032120 | null | q-bio.BM physics.bio-ph quant-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We investigate, using the Hierarchy method, the entanglement and the
excitation transfer efficiency of the Fenna-Matthews-Olson complex under two
different local modifications: the suppression of transitions between
particular sites and localized changes to the protein environment. We find that
inhibiting the connection between the site-5 and site-6, or disconnecting
site-5 from the complex completely, leads to an dramatic enhancement of the
entanglement between site-6 and site-7. Similarly, the transfer efficiency
actually increases if site-5 is disconnected from the complex entirely. We
further show that if site-5 and site-7 are conjointly removed, the efficiency
falls. This suggests that while not contributing to the transport efficiency in
a normal complex, site-5 introduces a redundant transport route in case of
damage to site-7. Our results suggest an overall robustness of excitation
energy transfer in the FMO complex under mutations, local defects, and other
abnormal situations.
| [
{
"created": "Tue, 9 Apr 2013 14:38:10 GMT",
"version": "v1"
}
] | 2013-10-24 | [
[
"Chen",
"Guang-Yin",
""
],
[
"Lambert",
"Neill",
""
],
[
"Li",
"Che-Ming",
""
],
[
"Chen",
"Yueh-Nan",
""
],
[
"Nori",
"Franco",
""
]
] | We investigate, using the Hierarchy method, the entanglement and the excitation transfer efficiency of the Fenna-Matthews-Olson complex under two different local modifications: the suppression of transitions between particular sites and localized changes to the protein environment. We find that inhibiting the connection between the site-5 and site-6, or disconnecting site-5 from the complex completely, leads to an dramatic enhancement of the entanglement between site-6 and site-7. Similarly, the transfer efficiency actually increases if site-5 is disconnected from the complex entirely. We further show that if site-5 and site-7 are conjointly removed, the efficiency falls. This suggests that while not contributing to the transport efficiency in a normal complex, site-5 introduces a redundant transport route in case of damage to site-7. Our results suggest an overall robustness of excitation energy transfer in the FMO complex under mutations, local defects, and other abnormal situations. |
1706.06914 | Mauro M. Monsalve-Mercado | Mauro M. Monsalve-Mercado, Christian Leibold | Hippocampal Spike-Timing Correlations Lead to Hexagonal Grid Fields | Accepted for publication in Physical Review Letters | null | 10.1103/PhysRevLett.119.038101 | null | q-bio.NC nlin.AO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Space is represented in the mammalian brain by the activity of hippocampal
place cells as well as in their spike-timing correlations. Here we propose a
theory how this temporal code is transformed to spatial firing rate patterns
via spike-timing-dependent synaptic plasticity. The resulting dynamics of
synaptic weights resembles well-known pattern formation models in which a
lateral inhibition mechanism gives rise to a Turing instability. We identify
parameter regimes in which hexagonal firing patterns develop as they have been
found in medial entorhinal cortex.
| [
{
"created": "Wed, 21 Jun 2017 14:05:52 GMT",
"version": "v1"
}
] | 2017-08-02 | [
[
"Monsalve-Mercado",
"Mauro M.",
""
],
[
"Leibold",
"Christian",
""
]
] | Space is represented in the mammalian brain by the activity of hippocampal place cells as well as in their spike-timing correlations. Here we propose a theory how this temporal code is transformed to spatial firing rate patterns via spike-timing-dependent synaptic plasticity. The resulting dynamics of synaptic weights resembles well-known pattern formation models in which a lateral inhibition mechanism gives rise to a Turing instability. We identify parameter regimes in which hexagonal firing patterns develop as they have been found in medial entorhinal cortex. |
q-bio/0701030 | Peter Csermely | Tamas Korcsmaros, Istvan A. Kovacs, Mate S. Szalay and Peter Csermely | Molecular chaperones: The modular evolution of cellular networks | 7 pages, 3 tables, 3 figures | J. Biosciences (2007) 32, 441-446 | null | null | q-bio.MN | null | Molecular chaperones play a prominent role in signaling and transcriptional
regulatory networks of the cell. Recent advances uncovered that chaperones act
as genetic buffers stabilizing the phenotype of various cells and organisms and
may serve as potential regulators of evolvability. Chaperones have weak links,
connect hubs, are in the overlaps of network modules and may uncouple these
modules during stress, which gives an additional protection for the cell at the
network-level. Moreover, after stress chaperones are essential to re-build
inter-modular contacts by their low affinity sampling of the potential
interaction partners in different modules. This opens the way to the
chaperone-regulated modular evolution of cellular networks, and helps us to
design novel therapeutic and anti-aging strategies.
| [
{
"created": "Fri, 19 Jan 2007 10:04:11 GMT",
"version": "v1"
},
{
"created": "Mon, 30 Apr 2007 16:26:39 GMT",
"version": "v2"
}
] | 2007-05-23 | [
[
"Korcsmaros",
"Tamas",
""
],
[
"Kovacs",
"Istvan A.",
""
],
[
"Szalay",
"Mate S.",
""
],
[
"Csermely",
"Peter",
""
]
] | Molecular chaperones play a prominent role in signaling and transcriptional regulatory networks of the cell. Recent advances uncovered that chaperones act as genetic buffers stabilizing the phenotype of various cells and organisms and may serve as potential regulators of evolvability. Chaperones have weak links, connect hubs, are in the overlaps of network modules and may uncouple these modules during stress, which gives an additional protection for the cell at the network-level. Moreover, after stress chaperones are essential to re-build inter-modular contacts by their low affinity sampling of the potential interaction partners in different modules. This opens the way to the chaperone-regulated modular evolution of cellular networks, and helps us to design novel therapeutic and anti-aging strategies. |
1611.02276 | James Peters Ph.D. | Arturo Tozzi and James F. Peters and Ottorino Ori | Towards the neural code endowed in cortical microcolumns | 11 pages, 5 figures | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This article reports on simulations that show how, starting with a form of
neural lattice structure, it is possible to reversibly generate many
alternative isomers with a lower structural symmetry, which results from
twisting two hexagons around a central bond.
| [
{
"created": "Mon, 7 Nov 2016 18:33:00 GMT",
"version": "v1"
}
] | 2016-11-09 | [
[
"Tozzi",
"Arturo",
""
],
[
"Peters",
"James F.",
""
],
[
"Ori",
"Ottorino",
""
]
] | This article reports on simulations that show how, starting with a form of neural lattice structure, it is possible to reversibly generate many alternative isomers with a lower structural symmetry, which results from twisting two hexagons around a central bond. |
2107.07862 | Samitha Somathilaka | Samitha Somathilaka, Daniel P. Martins, Wiley Barton, Orla O'Sullivan,
Paul D. Cotter, Sasitharan Balasubramaniam | A Graph-based Molecular Communications Model Analysis of the Human Gut
Bacteriome | null | null | null | null | q-bio.MN cs.ET | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Alterations in the human gut bacteriome can be associated with human health
issues, such as type-2 diabetes and cardiovascular disease. Both external and
internal factors can drive changes in the composition and in the interactions
of the human gut bacteriome, impacting negatively on the host cells. In this
paper, we focus on the human gut bacteriome metabolism and we propose a
two-layer network system to investigate its dynamics. Furthermore, we develop
an in-silico simulation model (virtual GB), allowing us to study the impact of
the metabolite exchange through molecular communications in the human gut
bacteriome network system. Our results show that the regulation of molecular
inputs can strongly affect bacterial population growth and create an unbalanced
network, as shown by the shift in the node weights based on the molecular
signals that are produced. Additionally, we show that the metabolite molecular
communication production is greatly affected when directly manipulating the
composition of the human gut bacteriome network in the virtual GB. These
results indicate that our human GB interaction model can help to identify
hidden behaviors of the human gut bacteriome depending on the molecular signal
interactions. Moreover, the virtual GB can support the research and development
of novel medical treatments based on the accurate control of bacterial growth
and exchange of metabolites.
| [
{
"created": "Fri, 16 Jul 2021 12:56:03 GMT",
"version": "v1"
}
] | 2021-07-19 | [
[
"Somathilaka",
"Samitha",
""
],
[
"Martins",
"Daniel P.",
""
],
[
"Barton",
"Wiley",
""
],
[
"O'Sullivan",
"Orla",
""
],
[
"Cotter",
"Paul D.",
""
],
[
"Balasubramaniam",
"Sasitharan",
""
]
] | Alterations in the human gut bacteriome can be associated with human health issues, such as type-2 diabetes and cardiovascular disease. Both external and internal factors can drive changes in the composition and in the interactions of the human gut bacteriome, impacting negatively on the host cells. In this paper, we focus on the human gut bacteriome metabolism and we propose a two-layer network system to investigate its dynamics. Furthermore, we develop an in-silico simulation model (virtual GB), allowing us to study the impact of the metabolite exchange through molecular communications in the human gut bacteriome network system. Our results show that the regulation of molecular inputs can strongly affect bacterial population growth and create an unbalanced network, as shown by the shift in the node weights based on the molecular signals that are produced. Additionally, we show that the metabolite molecular communication production is greatly affected when directly manipulating the composition of the human gut bacteriome network in the virtual GB. These results indicate that our human GB interaction model can help to identify hidden behaviors of the human gut bacteriome depending on the molecular signal interactions. Moreover, the virtual GB can support the research and development of novel medical treatments based on the accurate control of bacterial growth and exchange of metabolites. |
2004.01399 | Irina Mizeva | Andrey Shmyrov, Alexey Mizev, Irina Mizeva and Anastasia Shmyrova | Electrostatic precipitation of exhaled particles for tensiometric
examination of pulmonary surfactant | 19 pages, 6 figures, submitted | null | null | null | q-bio.TO physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Objective: Collecting exhaled particles that represent small droplets of the
alveolar lining fluid shows great promise as a tool for pulmonary surfactant
(PS) sampling. For this purpose, we present a setup consisting of two modules,
namely, a module for droplet collecting, called an electrostatic aerosol
trapping (ESAT) system, and a measurement module for studying PS properties. We
suggest the way how to extract numerical values from the experimental data
associated with PS properties.
Methods: The operating principle of ESAT is based on the electrostatic
precipitation of exhaled particles. The native material was collected directly
on the water surface, where an accumulated adsorbed film of PS was examined
with tensiometric method. The modified capillary waves method adapted to study
small volume samples was utilized. The efficiency of the setup was verified in
the experiments with healthy subjects.
Conclusion: The accumulation of PS components on the water surface in an
amount sufficient for tensiometric study was reported. It was shown how to
extract the numerical values from the experimental data characterizing PS
properties.
Significance: The idea underlying the new concept used in this study may give
impetus to further development of point-of-care facilities for collecting PS
samples and for their express analysis.
| [
{
"created": "Fri, 3 Apr 2020 06:55:55 GMT",
"version": "v1"
}
] | 2020-04-06 | [
[
"Shmyrov",
"Andrey",
""
],
[
"Mizev",
"Alexey",
""
],
[
"Mizeva",
"Irina",
""
],
[
"Shmyrova",
"Anastasia",
""
]
] | Objective: Collecting exhaled particles that represent small droplets of the alveolar lining fluid shows great promise as a tool for pulmonary surfactant (PS) sampling. For this purpose, we present a setup consisting of two modules, namely, a module for droplet collecting, called an electrostatic aerosol trapping (ESAT) system, and a measurement module for studying PS properties. We suggest the way how to extract numerical values from the experimental data associated with PS properties. Methods: The operating principle of ESAT is based on the electrostatic precipitation of exhaled particles. The native material was collected directly on the water surface, where an accumulated adsorbed film of PS was examined with tensiometric method. The modified capillary waves method adapted to study small volume samples was utilized. The efficiency of the setup was verified in the experiments with healthy subjects. Conclusion: The accumulation of PS components on the water surface in an amount sufficient for tensiometric study was reported. It was shown how to extract the numerical values from the experimental data characterizing PS properties. Significance: The idea underlying the new concept used in this study may give impetus to further development of point-of-care facilities for collecting PS samples and for their express analysis. |
1301.6357 | Tomasz Rutkowski | H. Mori, Y. Matsumoto, Z. R. Struzik, K. Mori, S. Makino, D. Mandic,
and T.M. Rutkowski | Multi-command Tactile and Auditory Brain Computer Interface based on
Head Position Stimulation | Proceedings of the Fifth International Brain-Computer Interface
Meeting 2013, 2 pages, 1 figure | null | 10.3217/978-4-83452-381-5/095 | null | q-bio.NC cs.HC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the extent to which vibrotactile stimuli delivered to the head of a
subject can serve as a platform for a brain computer interface (BCI) paradigm.
Six head positions are used to evoke combined somatosensory and auditory (via
the bone conduction effect) brain responses, in order to define a multimodal
tactile and auditory brain computer interface (taBCI). Experimental results of
subjects performing online taBCI, using stimuli with a moderately fast
inter-stimulus interval (ISI), validate the taBCI paradigm, while the
feasibility of the concept is illuminated through information transfer rate
case studies.
| [
{
"created": "Sun, 27 Jan 2013 14:18:04 GMT",
"version": "v1"
},
{
"created": "Sun, 12 May 2013 06:31:51 GMT",
"version": "v2"
}
] | 2013-05-14 | [
[
"Mori",
"H.",
""
],
[
"Matsumoto",
"Y.",
""
],
[
"Struzik",
"Z. R.",
""
],
[
"Mori",
"K.",
""
],
[
"Makino",
"S.",
""
],
[
"Mandic",
"D.",
""
],
[
"Rutkowski",
"T. M.",
""
]
] | We study the extent to which vibrotactile stimuli delivered to the head of a subject can serve as a platform for a brain computer interface (BCI) paradigm. Six head positions are used to evoke combined somatosensory and auditory (via the bone conduction effect) brain responses, in order to define a multimodal tactile and auditory brain computer interface (taBCI). Experimental results of subjects performing online taBCI, using stimuli with a moderately fast inter-stimulus interval (ISI), validate the taBCI paradigm, while the feasibility of the concept is illuminated through information transfer rate case studies. |
1909.04206 | Yu-Ting Lin | Shen-Chih Wang, Hau-Tieng Wu, Po-Hsun Huang, Cheng-Hsi Chang,
Chien-Kun Ting, Yu-Ting Lin | Novel imaging revealing inner dynamics for cardiovascular waveform
analysis via unsupervised manifold learning | 36 pages, 6 figures | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cardiovascular waveforms contain information for clinical diagnosis. By
"learning" and organizing the subtle change of waveform morphology from large
amounts of raw waveform data, unsupervised manifold learning helps delineate a
high-dimensional structure and display it as a novel three-dimensional (3D)
image. We investigate the electrocardiography (ECG) waveform for ischemic heart
disease and arterial blood pressure (ABP) waveform in dynamic vasoactive
episodes. We model each beat or pulse to be a point lying on a manifold, like a
surface, and use the diffusion map (DMap) to establish the relationship among
those pulses. For ECG datasets, first we analyzed the non-ST-elevation ECG
waveform distribution from unstable angina to healthy control, and we
investigated intraoperative ST-elevation ECG waveforms to show the dynamic ECG
waveform changes. For ABP datasets, we analyzed waveforms collected under
endotracheal intubation and administration of vasodilator. To quantify the
dynamic separation, we applied the support vector machine (SVM) analysis and
the trajectory analysis. For the non-ST-elevation ECG, a hierarchical tree
structure comprising consecutive ECG waveforms spanning from unstable angina to
healthy control is presented in the 3D image (accuracy=97.6%, macro-F1=96.1%).
The DMap helps quantify and visualize the evolving direction of intraoperative
ST-elevation myocardial episode in a 1-hour period (accuracy=97.58%,
macro-F1=96.06%). The ABP waveform analysis of Nicardipine administration shows
inter-individual difference (accuracy=95.01%, macro-F1=96.9%) and their common
directions from intra-individual moving trajectories. The dynamic change of the
ABP waveform during endotracheal intubation shows a loop-like trajectory
structure, which can be further divided using the knowledge obtained from
Nicardipine. The 3D images provide clues of underneath physiological
mechanisms.
| [
{
"created": "Tue, 10 Sep 2019 00:41:33 GMT",
"version": "v1"
},
{
"created": "Mon, 2 Dec 2019 06:06:10 GMT",
"version": "v2"
}
] | 2019-12-03 | [
[
"Wang",
"Shen-Chih",
""
],
[
"Wu",
"Hau-Tieng",
""
],
[
"Huang",
"Po-Hsun",
""
],
[
"Chang",
"Cheng-Hsi",
""
],
[
"Ting",
"Chien-Kun",
""
],
[
"Lin",
"Yu-Ting",
""
]
] | Cardiovascular waveforms contain information for clinical diagnosis. By "learning" and organizing the subtle change of waveform morphology from large amounts of raw waveform data, unsupervised manifold learning helps delineate a high-dimensional structure and display it as a novel three-dimensional (3D) image. We investigate the electrocardiography (ECG) waveform for ischemic heart disease and arterial blood pressure (ABP) waveform in dynamic vasoactive episodes. We model each beat or pulse to be a point lying on a manifold, like a surface, and use the diffusion map (DMap) to establish the relationship among those pulses. For ECG datasets, first we analyzed the non-ST-elevation ECG waveform distribution from unstable angina to healthy control, and we investigated intraoperative ST-elevation ECG waveforms to show the dynamic ECG waveform changes. For ABP datasets, we analyzed waveforms collected under endotracheal intubation and administration of vasodilator. To quantify the dynamic separation, we applied the support vector machine (SVM) analysis and the trajectory analysis. For the non-ST-elevation ECG, a hierarchical tree structure comprising consecutive ECG waveforms spanning from unstable angina to healthy control is presented in the 3D image (accuracy=97.6%, macro-F1=96.1%). The DMap helps quantify and visualize the evolving direction of intraoperative ST-elevation myocardial episode in a 1-hour period (accuracy=97.58%, macro-F1=96.06%). The ABP waveform analysis of Nicardipine administration shows inter-individual difference (accuracy=95.01%, macro-F1=96.9%) and their common directions from intra-individual moving trajectories. The dynamic change of the ABP waveform during endotracheal intubation shows a loop-like trajectory structure, which can be further divided using the knowledge obtained from Nicardipine. The 3D images provide clues of underneath physiological mechanisms. |
1009.3607 | Kevin E. Cahill | Kevin Cahill | Simple Model of the Transduction of Cell-Penetrating Peptides | Seven pages. For a more complete version including the effects of
counterions, see arXiv:0810.2358v3 [q-bio.BM] | IET Syst. Biol., 2009, Vol. 3, Iss. 5, pp. 300- 306 | 10.1049/iet-syb.2008.0160 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cell-penetrating peptides (CPPs) such as HIV's trans-activating
transcriptional activator (TAT) and polyarginine rapidly pass through the
plasma membranes of mammalian cells by an unknown mechanism called
transduction. They may be medically useful when fused to well-chosen chains of
fewer than about 35 amino acids. I offer a simple model of transduction in
which phosphatidylserines and CPPs effectively form two plates of a capacitor
with a voltage sufficient to cause the formation of transient pores
(electroporation). The model is consistent with experimental data on the
transduction of oligoarginine into mouse C2-C12 myoblasts and makes three
testable predictions.
| [
{
"created": "Sun, 19 Sep 2010 04:34:30 GMT",
"version": "v1"
}
] | 2010-09-21 | [
[
"Cahill",
"Kevin",
""
]
] | Cell-penetrating peptides (CPPs) such as HIV's trans-activating transcriptional activator (TAT) and polyarginine rapidly pass through the plasma membranes of mammalian cells by an unknown mechanism called transduction. They may be medically useful when fused to well-chosen chains of fewer than about 35 amino acids. I offer a simple model of transduction in which phosphatidylserines and CPPs effectively form two plates of a capacitor with a voltage sufficient to cause the formation of transient pores (electroporation). The model is consistent with experimental data on the transduction of oligoarginine into mouse C2-C12 myoblasts and makes three testable predictions. |
1110.6538 | Ossnat Bar-Shira | Ossnat Bar-Shira and Gal Chechik | COLoR - Coordinated On-Line Rankers for Network Reconstruction | null | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Predicting protein interactions is one of the more interesting challenges of
the post-genomic era. Many algorithms address this problem as a binary
classification problem: given two proteins represented as two vectors of
features, predict if they interact or not. Importantly however, computational
predictions are only one component of a larger framework for identifying PPI.
The most promising candidate pairs can be validated experimentally by testing
if they physical bind to each other. Since these experiments are more costly
and error prone, the computational predictions serve as a filter, aimed to
produce a small number of highly promising candidates. Here we propose to
address this problem as a ranking problem: given a network with known
interactions, rank all unknown pairs based on the likelihood of their
interactions.
In this paper we propose a ranking algorithm that trains multiple
inter-connected models using a passive aggressive on-line approach. We show
good results predicting protein-protein interactions for post synaptic density
PPI network. We compare the precision of the ranking algorithm with local
classifiers and classic support vector machine. Though the ranking algorithm
outperforms the classic SVM classification, its performance is inferior
compared to the local supervised method.
| [
{
"created": "Sat, 29 Oct 2011 16:23:07 GMT",
"version": "v1"
}
] | 2011-11-01 | [
[
"Bar-Shira",
"Ossnat",
""
],
[
"Chechik",
"Gal",
""
]
] | Predicting protein interactions is one of the more interesting challenges of the post-genomic era. Many algorithms address this problem as a binary classification problem: given two proteins represented as two vectors of features, predict if they interact or not. Importantly however, computational predictions are only one component of a larger framework for identifying PPI. The most promising candidate pairs can be validated experimentally by testing if they physical bind to each other. Since these experiments are more costly and error prone, the computational predictions serve as a filter, aimed to produce a small number of highly promising candidates. Here we propose to address this problem as a ranking problem: given a network with known interactions, rank all unknown pairs based on the likelihood of their interactions. In this paper we propose a ranking algorithm that trains multiple inter-connected models using a passive aggressive on-line approach. We show good results predicting protein-protein interactions for post synaptic density PPI network. We compare the precision of the ranking algorithm with local classifiers and classic support vector machine. Though the ranking algorithm outperforms the classic SVM classification, its performance is inferior compared to the local supervised method. |
2209.09761 | Mario Ignacio Simoy | Mario I. Simoy and Marcelo N. Kuperman | Non-local interaction effects in models of interacting populations | null | null | null | null | q-bio.PE math.DS nlin.PS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider a couple of models for the dynamics of the populations of two
interacting species, inspired by Lotka-Volterra's classical equations. The
novelty of this work is that the interaction terms are non local and the
interaction occurs within a bounded range. These terms include the competitive
intraspecific interaction among individuals and the interspecific terms for
which we consider two cases: Competition and predation. The results show that
not only the non-locality induces spatial structures but also allows for the
survival of the species when due to predation or the competitive exclusion
extinction was expected, and even promotes spatio-temporal patterns not linked
to eventual temporal oscillations in the local case. In this work we also
explore some interesting details about the behavior of the population dynamics
that shows spatial patterns that interfere in a way that leads to non-trivial
results.
| [
{
"created": "Tue, 20 Sep 2022 14:43:21 GMT",
"version": "v1"
}
] | 2022-09-21 | [
[
"Simoy",
"Mario I.",
""
],
[
"Kuperman",
"Marcelo N.",
""
]
] | We consider a couple of models for the dynamics of the populations of two interacting species, inspired by Lotka-Volterra's classical equations. The novelty of this work is that the interaction terms are non local and the interaction occurs within a bounded range. These terms include the competitive intraspecific interaction among individuals and the interspecific terms for which we consider two cases: Competition and predation. The results show that not only the non-locality induces spatial structures but also allows for the survival of the species when due to predation or the competitive exclusion extinction was expected, and even promotes spatio-temporal patterns not linked to eventual temporal oscillations in the local case. In this work we also explore some interesting details about the behavior of the population dynamics that shows spatial patterns that interfere in a way that leads to non-trivial results. |
1604.04786 | German Mi\~no Dr | German Mi\~no-Galaz, Junia Melin, Gonzalo Gutierrez, Felipe Bravo,
Valeria Marquez and Fernando Gonzalez-Nilo | On the Asymmetry of Vibrational Energy Flow | null | null | null | null | q-bio.BM physics.chem-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A simple model to predict the directionality of vibrational energy flow at
molecular level is presented. This model is based on a vibrational energy
propagation analysis using ab intio molecular dynamics and the Fukui function
and local softness reactivity indexes derived from DFT. By using this simple
conceptual model we are giving a cogent rationale to previous theoretical and
experimental reports of asymmetrical vibrational energy diffusion in proteins
and energetic materials. We proposed here three basic rules for the Vibrational
Energy Relaxation in molecules: (i) the vibrational energy flows form a soft
site to a hard site but not in the opposite direction, (ii) when vibrational
energy is injected directly to a hard site, it is trapped in this site, and
(iii) if the vibrational energy is pump in a polarizable site and two sites
with different softness are available, the energy will propagate to the softest
one.
| [
{
"created": "Sat, 16 Apr 2016 18:44:20 GMT",
"version": "v1"
}
] | 2016-04-19 | [
[
"Miño-Galaz",
"German",
""
],
[
"Melin",
"Junia",
""
],
[
"Gutierrez",
"Gonzalo",
""
],
[
"Bravo",
"Felipe",
""
],
[
"Marquez",
"Valeria",
""
],
[
"Gonzalez-Nilo",
"Fernando",
""
]
] | A simple model to predict the directionality of vibrational energy flow at molecular level is presented. This model is based on a vibrational energy propagation analysis using ab intio molecular dynamics and the Fukui function and local softness reactivity indexes derived from DFT. By using this simple conceptual model we are giving a cogent rationale to previous theoretical and experimental reports of asymmetrical vibrational energy diffusion in proteins and energetic materials. We proposed here three basic rules for the Vibrational Energy Relaxation in molecules: (i) the vibrational energy flows form a soft site to a hard site but not in the opposite direction, (ii) when vibrational energy is injected directly to a hard site, it is trapped in this site, and (iii) if the vibrational energy is pump in a polarizable site and two sites with different softness are available, the energy will propagate to the softest one. |
1605.07796 | Mark Leake | Anjana Badrinarayanan, Mark C. Leake | Using Fluorescence Recovery After Photobleaching (FRAP) to study
dynamics of the Structural Maintenance of Chromosome (SMC) complex in vivo | null | null | null | null | q-bio.SC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The SMC complex, MukBEF, is important for chromosome organization and
segregation in Escherichia coli. Fluorescently tagged MukBEF forms distinct
spots (or 'foci') in the cell, where it is thought to carry out most of its
chromosome associated activities. This chapter outlines the technique of
Fluorescence Recovery After Photobleaching (FRAP) as a method to study the
properties of YFP-tagged MukB in fluorescent foci. This method can provide
important insight into the dynamics of MukB on DNA and be used to study its
biochemical properties in vivo.
| [
{
"created": "Wed, 25 May 2016 09:28:47 GMT",
"version": "v1"
}
] | 2016-06-09 | [
[
"Badrinarayanan",
"Anjana",
""
],
[
"Leake",
"Mark C.",
""
]
] | The SMC complex, MukBEF, is important for chromosome organization and segregation in Escherichia coli. Fluorescently tagged MukBEF forms distinct spots (or 'foci') in the cell, where it is thought to carry out most of its chromosome associated activities. This chapter outlines the technique of Fluorescence Recovery After Photobleaching (FRAP) as a method to study the properties of YFP-tagged MukB in fluorescent foci. This method can provide important insight into the dynamics of MukB on DNA and be used to study its biochemical properties in vivo. |
1502.01241 | Reza Ebrahimpour | Amirhossein Farzmahdi, Karim Rajaei, Masoud Ghodrati, Reza
Ebrahimpour, Seyed-Mahdi Khaligh-Razavi | A specialized face-processing network consistent with the
representational geometry of monkey face patches | 41 pages, 12 figures | null | null | null | q-bio.NC cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Ample evidence suggests that face processing in human and non-human primates
is performed differently compared with other objects. Converging reports, both
physiologically and psychophysically, indicate that faces are processed in
specialized neural networks in the brain -i.e. face patches in monkeys and the
fusiform face area (FFA) in humans. We are all expert face-processing agents,
and able to identify very subtle differences within the category of faces,
despite substantial visual and featural similarities. Identification is
performed rapidly and accurately after viewing a whole face, while
significantly drops if some of the face configurations (e.g. inversion,
misalignment) are manipulated or if partial views of faces are shown due to
occlusion. This refers to a hotly-debated, yet highly-supported concept, known
as holistic face processing. We built a hierarchical computational model of
face-processing based on evidence from recent neuronal and behavioural studies
on faces processing in primates. Representational geometries of the last three
layers of the model have characteristics similar to those observed in monkey
face patches (posterior, middle and anterior patches). Furthermore, several
face-processing-related phenomena reported in the literature automatically
emerge as properties of this model. The representations are evolved through
several computational layers, using biologically plausible learning rules. The
model satisfies face inversion effect, composite face effect, other race
effect, view and identity selectivity, and canonical face views. To our
knowledge, no models have so far been proposed with this performance and
agreement with biological data.
| [
{
"created": "Wed, 4 Feb 2015 15:50:11 GMT",
"version": "v1"
},
{
"created": "Thu, 5 Feb 2015 12:55:58 GMT",
"version": "v2"
},
{
"created": "Sun, 30 Oct 2016 15:47:46 GMT",
"version": "v3"
}
] | 2016-11-01 | [
[
"Farzmahdi",
"Amirhossein",
""
],
[
"Rajaei",
"Karim",
""
],
[
"Ghodrati",
"Masoud",
""
],
[
"Ebrahimpour",
"Reza",
""
],
[
"Khaligh-Razavi",
"Seyed-Mahdi",
""
]
] | Ample evidence suggests that face processing in human and non-human primates is performed differently compared with other objects. Converging reports, both physiologically and psychophysically, indicate that faces are processed in specialized neural networks in the brain -i.e. face patches in monkeys and the fusiform face area (FFA) in humans. We are all expert face-processing agents, and able to identify very subtle differences within the category of faces, despite substantial visual and featural similarities. Identification is performed rapidly and accurately after viewing a whole face, while significantly drops if some of the face configurations (e.g. inversion, misalignment) are manipulated or if partial views of faces are shown due to occlusion. This refers to a hotly-debated, yet highly-supported concept, known as holistic face processing. We built a hierarchical computational model of face-processing based on evidence from recent neuronal and behavioural studies on faces processing in primates. Representational geometries of the last three layers of the model have characteristics similar to those observed in monkey face patches (posterior, middle and anterior patches). Furthermore, several face-processing-related phenomena reported in the literature automatically emerge as properties of this model. The representations are evolved through several computational layers, using biologically plausible learning rules. The model satisfies face inversion effect, composite face effect, other race effect, view and identity selectivity, and canonical face views. To our knowledge, no models have so far been proposed with this performance and agreement with biological data. |
q-bio/0607008 | Dagmar Iber | Dagmar Iber | A quantitative study of the benefits of co-regulation using the spoIIA
operon as an example | null | null | null | null | q-bio.MN q-bio.PE | null | The distribution of most genes is not random, and functionally linked genes
are often found in clusters. Several theories have been put forward to explain
the emergence and persistence of operons in bacteria. Careful analysis of
genomic data favours the co-regulation model, where gene organization into
operons is driven by the benefits of coordinated gene expression and
regulation. Direct evidence that co-expression increases the individual's
fitness enough to ensure operon formation and maintenance is, however, still
lacking. Here, a previously described quantitative model of the network that
controls the transcription factor sigmaF during sporulation in Bacillus
subtilis is employed to quantify the benefits arising from both organisation of
the sporulation genes into the spoIIA operon and from translational coupling.
The analysis shows that operon organization, together with translational
coupling, is important because of the inherent stochastic nature of gene
expression which skews the ratios between protein concentrations in the absence
of co- regulation. The predicted impact of different forms of gene regulation
on fitness and survival agrees quantitatively with published sporulation
efficiencies.
| [
{
"created": "Wed, 5 Jul 2006 11:14:56 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Iber",
"Dagmar",
""
]
] | The distribution of most genes is not random, and functionally linked genes are often found in clusters. Several theories have been put forward to explain the emergence and persistence of operons in bacteria. Careful analysis of genomic data favours the co-regulation model, where gene organization into operons is driven by the benefits of coordinated gene expression and regulation. Direct evidence that co-expression increases the individual's fitness enough to ensure operon formation and maintenance is, however, still lacking. Here, a previously described quantitative model of the network that controls the transcription factor sigmaF during sporulation in Bacillus subtilis is employed to quantify the benefits arising from both organisation of the sporulation genes into the spoIIA operon and from translational coupling. The analysis shows that operon organization, together with translational coupling, is important because of the inherent stochastic nature of gene expression which skews the ratios between protein concentrations in the absence of co- regulation. The predicted impact of different forms of gene regulation on fitness and survival agrees quantitatively with published sporulation efficiencies. |
1712.02626 | Vitor Manuel Dinis Pereira | Vitor Manuel Dinis Pereira | Occipital and left temporal EEG correlates of phenomenal consciousness | 25 pages, 30 figures, chapter book, (2015).Tran, Q-N. and Arabnia,
H.R. (eds.). Emerging Trends in Computational Biology, Bioinformatics, and
Systems Biology. Elsevier/Morgan Kaufmann | null | 10.1016/b978-0-12-802508-6.00018-1 | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | In the first section, Introduction, we present our experimental design. In
the second section, we characterize the grand average occipital and temporal
electrical activity correlated with a contrast in access. In the third section,
we characterize the grand average occipital and temporal electrical activity
correlated with a contrast in phenomenology and conclude characterizing the
grand average occipital and temporal electrical activity co-occurring with
unconsciousness.
| [
{
"created": "Sun, 5 Nov 2017 00:43:09 GMT",
"version": "v1"
},
{
"created": "Sun, 1 Nov 2020 14:58:08 GMT",
"version": "v2"
},
{
"created": "Sat, 26 Dec 2020 17:16:19 GMT",
"version": "v3"
}
] | 2020-12-29 | [
[
"Pereira",
"Vitor Manuel Dinis",
""
]
] | In the first section, Introduction, we present our experimental design. In the second section, we characterize the grand average occipital and temporal electrical activity correlated with a contrast in access. In the third section, we characterize the grand average occipital and temporal electrical activity correlated with a contrast in phenomenology and conclude characterizing the grand average occipital and temporal electrical activity co-occurring with unconsciousness. |
1411.1572 | Philippe Robert S. | Vincent Fromion and Emanuele Leoncini and Philippe Robert | A stochastic model of the production of multiple proteins in cells | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The production processes of proteins in prokaryotic cells are investigated.
Most of the mathematical models in the literature study the production of {\em
one} fixed type of proteins. When several classes of proteins are considered,
an important additional aspect has to be taken into account, the limited common
resources of the cell (polymerases and ribosomes) used by the production
process. Understanding the impact of this limitation is a key issue in this
domain. In this paper we focus on the allocation of ribosomes in the case of
the production of multiple proteins. The cytoplasm of the cell being a
disorganized medium subject to thermal noise, the protein production process
has an important stochastic component. For this reason, a Markovian model of
this process is introduced. Asymptotic results of the equilibrium are obtained
under a scaling procedure and a realistic biological assumption of saturation
of the ribosomes available in the cell. It is shown in particular that, in the
limit, the number of non-allocated ribosomes at equilibrium converges in
distribution to a Poisson distribution whose parameter satisfies a fixed point
equation. It is also shown that the production process of different types of
proteins can be seen as independent production processes but with modified
parameters.
| [
{
"created": "Thu, 6 Nov 2014 11:31:56 GMT",
"version": "v1"
}
] | 2014-11-07 | [
[
"Fromion",
"Vincent",
""
],
[
"Leoncini",
"Emanuele",
""
],
[
"Robert",
"Philippe",
""
]
] | The production processes of proteins in prokaryotic cells are investigated. Most of the mathematical models in the literature study the production of {\em one} fixed type of proteins. When several classes of proteins are considered, an important additional aspect has to be taken into account, the limited common resources of the cell (polymerases and ribosomes) used by the production process. Understanding the impact of this limitation is a key issue in this domain. In this paper we focus on the allocation of ribosomes in the case of the production of multiple proteins. The cytoplasm of the cell being a disorganized medium subject to thermal noise, the protein production process has an important stochastic component. For this reason, a Markovian model of this process is introduced. Asymptotic results of the equilibrium are obtained under a scaling procedure and a realistic biological assumption of saturation of the ribosomes available in the cell. It is shown in particular that, in the limit, the number of non-allocated ribosomes at equilibrium converges in distribution to a Poisson distribution whose parameter satisfies a fixed point equation. It is also shown that the production process of different types of proteins can be seen as independent production processes but with modified parameters. |
1912.10749 | Muhammad Saif-Ur-Rehman | Muhammad Saif-ur-Rehman, Omair Ali, Robin Lienkaemper, Sussane Dyck,
Marita Metzler, Yaroslav Parpaley, Joerg Wellmer, Charles Liu, Brian Lee,
Spencer Kellis, Richard Andersen, Ioannis Iossifidis, Tobias Glasmachers,
Christian Klaes | SpikeDeep-Classifier: A deep-learning based fully automatic offline
spike sorting algorithm | 33 Pages, 14 Figures, 10 Tables | null | 10.1088/1741-2552/abc8d4 | null | q-bio.QM eess.SP q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Objective. Recent advancements in electrode designs and micro-fabrication
technology has allowed existence of microelectrode arrays with hundreds of
channels for single-cell recordings. In such electrophysiological recordings,
each implanted micro-electrode can record the activities of more than one
neuron in its vicinity. Recording the activities of multiple neurons may also
be referred to as multiple unit activity. However, for any further analysis,
the main goal is to isolate the activity of each recorded neuron and thus
called single-unit activity. This process may also be referred to as spike
sorting or spike classification. Recent approaches to extract SUA are time
consuming, mainly due to the requirement of human intervention at various
stages of spike sorting pipeline. Lack of standardization is another drawback
of the current available approaches. Therefore, in this study we proposed a
standard spike sorter: SpikeDeep-Classifier, a fully automatic spike sorting
algorithm. Approach. We proposed a novel spike sorting pipeline, based on a set
of supervised and unsupervised learning algorithms. We used supervised, deep
learning-based algorithms for extracting meaningful channels and removing
background activities (noise) from the extracted channels. We also showed that
the process of clustering becomes straight-forward, once the noise/artifact is
completely removed from the data. Therefore, in the next stage, we applied a
simple clustering algorithm (K-mean) with predefined maximum number of
clusters. Lastly, we used a similarity-based criterion to keep distinct
clusters and merge similar-looking clusters. Main results. We evaluated our
algorithm on a dataset collected from two different species (humans and
non-human primates (NHPs)) without any retraining. We also validated our
algorithm on two publicly available labeled datasets.
| [
{
"created": "Mon, 23 Dec 2019 11:42:16 GMT",
"version": "v1"
}
] | 2020-12-01 | [
[
"Saif-ur-Rehman",
"Muhammad",
""
],
[
"Ali",
"Omair",
""
],
[
"Lienkaemper",
"Robin",
""
],
[
"Dyck",
"Sussane",
""
],
[
"Metzler",
"Marita",
""
],
[
"Parpaley",
"Yaroslav",
""
],
[
"Wellmer",
"Joerg",
""
],
[
"Liu",
"Charles",
""
],
[
"Lee",
"Brian",
""
],
[
"Kellis",
"Spencer",
""
],
[
"Andersen",
"Richard",
""
],
[
"Iossifidis",
"Ioannis",
""
],
[
"Glasmachers",
"Tobias",
""
],
[
"Klaes",
"Christian",
""
]
] | Objective. Recent advancements in electrode designs and micro-fabrication technology has allowed existence of microelectrode arrays with hundreds of channels for single-cell recordings. In such electrophysiological recordings, each implanted micro-electrode can record the activities of more than one neuron in its vicinity. Recording the activities of multiple neurons may also be referred to as multiple unit activity. However, for any further analysis, the main goal is to isolate the activity of each recorded neuron and thus called single-unit activity. This process may also be referred to as spike sorting or spike classification. Recent approaches to extract SUA are time consuming, mainly due to the requirement of human intervention at various stages of spike sorting pipeline. Lack of standardization is another drawback of the current available approaches. Therefore, in this study we proposed a standard spike sorter: SpikeDeep-Classifier, a fully automatic spike sorting algorithm. Approach. We proposed a novel spike sorting pipeline, based on a set of supervised and unsupervised learning algorithms. We used supervised, deep learning-based algorithms for extracting meaningful channels and removing background activities (noise) from the extracted channels. We also showed that the process of clustering becomes straight-forward, once the noise/artifact is completely removed from the data. Therefore, in the next stage, we applied a simple clustering algorithm (K-mean) with predefined maximum number of clusters. Lastly, we used a similarity-based criterion to keep distinct clusters and merge similar-looking clusters. Main results. We evaluated our algorithm on a dataset collected from two different species (humans and non-human primates (NHPs)) without any retraining. We also validated our algorithm on two publicly available labeled datasets. |
1104.0910 | Michael Sheinman | M. Sheinman, O. B\'enichou, Y. Kafri and R. Voituriez | Classes of fast and specific search mechanisms for proteins on DNA | 65 pages, 23 figures | Rep. Prog. Phys. 75 (2012) 026601 | 10.1088/0034-4885/75/2/026601 | null | q-bio.BM cond-mat.soft physics.bio-ph q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Problems of search and recognition appear over different scales in biological
systems. In this review we focus on the challenges posed by interactions
between proteins, in particular transcription factors, and DNA and possible
mechanisms which allow for a fast and selective target location. Initially we
argue that DNA-binding proteins can be classified, broadly, into three distinct
classes which we illustrate using experimental data. Each class calls for a
different search process and we discuss the possible application of different
search mechanisms proposed over the years to each class. The main thrust of
this review is a new mechanism which is based on barrier discrimination. We
introduce the model and analyze in detail its consequences. It is shown that
this mechanism applies to all classes of transcription factors and can lead to
a fast and specific search. Moreover, it is shown that the mechanism has
interesting transient features which allow for stability at the target despite
rapid binding and unbinding of the transcription factor from the target.
| [
{
"created": "Tue, 5 Apr 2011 18:47:08 GMT",
"version": "v1"
}
] | 2015-03-19 | [
[
"Sheinman",
"M.",
""
],
[
"Bénichou",
"O.",
""
],
[
"Kafri",
"Y.",
""
],
[
"Voituriez",
"R.",
""
]
] | Problems of search and recognition appear over different scales in biological systems. In this review we focus on the challenges posed by interactions between proteins, in particular transcription factors, and DNA and possible mechanisms which allow for a fast and selective target location. Initially we argue that DNA-binding proteins can be classified, broadly, into three distinct classes which we illustrate using experimental data. Each class calls for a different search process and we discuss the possible application of different search mechanisms proposed over the years to each class. The main thrust of this review is a new mechanism which is based on barrier discrimination. We introduce the model and analyze in detail its consequences. It is shown that this mechanism applies to all classes of transcription factors and can lead to a fast and specific search. Moreover, it is shown that the mechanism has interesting transient features which allow for stability at the target despite rapid binding and unbinding of the transcription factor from the target. |
2312.04019 | Yijie Zhang | Yijie Zhang, Zhangyang Gao, Cheng Tan, Stan Z.Li | Efficiently Predicting Protein Stability Changes Upon Single-point
Mutation with Large Language Models | null | null | null | null | q-bio.BM cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Predicting protein stability changes induced by single-point mutations has
been a persistent challenge over the years, attracting immense interest from
numerous researchers. The ability to precisely predict protein thermostability
is pivotal for various subfields and applications in biochemistry, including
drug development, protein evolution analysis, and enzyme synthesis. Despite the
proposition of multiple methodologies aimed at addressing this issue, few
approaches have successfully achieved optimal performance coupled with high
computational efficiency. Two principal hurdles contribute to the existing
challenges in this domain. The first is the complexity of extracting and
aggregating sufficiently representative features from proteins. The second
refers to the limited availability of experimental data for protein mutation
analysis, further complicating the comprehensive evaluation of model
performance on unseen data samples. With the advent of Large Language
Models(LLM), such as the ESM models in protein research, profound
interpretation of protein features is now accessibly aided by enormous training
data. Therefore, LLMs are indeed to facilitate a wide range of protein
research. In our study, we introduce an ESM-assisted efficient approach that
integrates protein sequence and structural features to predict the
thermostability changes in protein upon single-point mutations. Furthermore, we
have curated a dataset meticulously designed to preclude data leakage,
corresponding to two extensively employed test datasets, to facilitate a more
equitable model comparison.
| [
{
"created": "Thu, 7 Dec 2023 03:25:49 GMT",
"version": "v1"
}
] | 2023-12-08 | [
[
"Zhang",
"Yijie",
""
],
[
"Gao",
"Zhangyang",
""
],
[
"Tan",
"Cheng",
""
],
[
"Li",
"Stan Z.",
""
]
] | Predicting protein stability changes induced by single-point mutations has been a persistent challenge over the years, attracting immense interest from numerous researchers. The ability to precisely predict protein thermostability is pivotal for various subfields and applications in biochemistry, including drug development, protein evolution analysis, and enzyme synthesis. Despite the proposition of multiple methodologies aimed at addressing this issue, few approaches have successfully achieved optimal performance coupled with high computational efficiency. Two principal hurdles contribute to the existing challenges in this domain. The first is the complexity of extracting and aggregating sufficiently representative features from proteins. The second refers to the limited availability of experimental data for protein mutation analysis, further complicating the comprehensive evaluation of model performance on unseen data samples. With the advent of Large Language Models(LLM), such as the ESM models in protein research, profound interpretation of protein features is now accessibly aided by enormous training data. Therefore, LLMs are indeed to facilitate a wide range of protein research. In our study, we introduce an ESM-assisted efficient approach that integrates protein sequence and structural features to predict the thermostability changes in protein upon single-point mutations. Furthermore, we have curated a dataset meticulously designed to preclude data leakage, corresponding to two extensively employed test datasets, to facilitate a more equitable model comparison. |
1409.6789 | John L. Rubinstein | John L. Rubinstein and Marcus A. Brubaker | Alignment of cryo-EM movies of individual particles by optimization of
image translations | 11 pages, 4 figures | J Struct Biol. 2015 Nov;192(2):188-95. doi:
10.1016/j.jsb.2015.08.007 | null | null | q-bio.QM physics.bio-ph q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Direct detector device (DDD) cameras have revolutionized single particle
electron cryomicroscopy (cryo-EM). In addition to an improved camera detective
quantum efficiency, acquisition of DDD movies allows for correction of movement
of the specimen, due both to instabilities in the microscope specimen stage and
electron beam-induced movement. Unlike specimen stage drift, beam-induced
movement is not always homogeneous within an image. Local correlation in the
trajectories of nearby particles suggests that beam-induced motion is due to
deformation of the ice layer. Algorithms have already been described that can
correct movement for large regions of frames and for > 1 MDa protein particles.
Another algorithm allows individual < 1 MDa protein particle trajectories to be
estimated, but requires rolling averages to be calculated from frames and fits
linear trajectories for particles. Here we describe an algorithm that allows
for individual < 1 MDa particle images to be aligned without frame averaging or
linear trajectories. The algorithm maximizes the overall correlation of the
shifted frames with the sum of the shifted frames. The optimum in this single
objective function is found efficiently by making use of analytically
calculated derivatives of the function. To smooth estimates of particle
trajectories, rapid changes in particle positions between frames are penalized
in the objective function and weighted averaging of nearby trajectories ensures
local correlation in trajectories. This individual particle motion correction,
in combination with weighting of Fourier components to account for increasing
radiation damage in later frames, can be used to improve 3-D maps from single
particle cryo-EM.
| [
{
"created": "Wed, 24 Sep 2014 01:24:12 GMT",
"version": "v1"
},
{
"created": "Tue, 3 Feb 2015 19:25:40 GMT",
"version": "v2"
},
{
"created": "Thu, 1 Oct 2015 02:24:05 GMT",
"version": "v3"
}
] | 2015-11-23 | [
[
"Rubinstein",
"John L.",
""
],
[
"Brubaker",
"Marcus A.",
""
]
] | Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM). In addition to an improved camera detective quantum efficiency, acquisition of DDD movies allows for correction of movement of the specimen, due both to instabilities in the microscope specimen stage and electron beam-induced movement. Unlike specimen stage drift, beam-induced movement is not always homogeneous within an image. Local correlation in the trajectories of nearby particles suggests that beam-induced motion is due to deformation of the ice layer. Algorithms have already been described that can correct movement for large regions of frames and for > 1 MDa protein particles. Another algorithm allows individual < 1 MDa protein particle trajectories to be estimated, but requires rolling averages to be calculated from frames and fits linear trajectories for particles. Here we describe an algorithm that allows for individual < 1 MDa particle images to be aligned without frame averaging or linear trajectories. The algorithm maximizes the overall correlation of the shifted frames with the sum of the shifted frames. The optimum in this single objective function is found efficiently by making use of analytically calculated derivatives of the function. To smooth estimates of particle trajectories, rapid changes in particle positions between frames are penalized in the objective function and weighted averaging of nearby trajectories ensures local correlation in trajectories. This individual particle motion correction, in combination with weighting of Fourier components to account for increasing radiation damage in later frames, can be used to improve 3-D maps from single particle cryo-EM. |
1404.0655 | Stephanie Elizabeth Palmer | Stephanie E. Palmer, Mimi H. Kao, Brian D. Wright, Allison J. Doupe | Temporal sequences of spikes during practice code for time in a complex
motor sequence | 24 pages, 10 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Practice of a complex motor gesture involves exploration of motor space to
attain a better match to target output, but little is known about the neural
code for such exploration. Here, we examine spiking in an area of the songbird
brain known to contribute to modification of song output. We find that neurons
in the outflow nucleus of a specialized basal ganglia- thalamocortical circuit,
the lateral magnocellular nucleus of the anterior nidopallium (LMAN), code for
time in the motor gesture (song) both during singing directed to a female bird
(performance) and when the bird sings alone (practice). Using mutual
information to quantify the correlation between temporal sequences of spikes
and time in song, we find that different symbols code for time in the two
singing states. While isolated spikes code for particular parts of song during
performance, extended strings of spiking and silence, particularly burst
events, code for time in song during practice. This temporal coding during
practice can be as precise as isolated spiking during performance to a female,
supporting the hypothesis that neurons in LMAN actively sample motor space,
guiding song modification at local instances in time.
| [
{
"created": "Wed, 2 Apr 2014 19:07:14 GMT",
"version": "v1"
}
] | 2014-04-03 | [
[
"Palmer",
"Stephanie E.",
""
],
[
"Kao",
"Mimi H.",
""
],
[
"Wright",
"Brian D.",
""
],
[
"Doupe",
"Allison J.",
""
]
] | Practice of a complex motor gesture involves exploration of motor space to attain a better match to target output, but little is known about the neural code for such exploration. Here, we examine spiking in an area of the songbird brain known to contribute to modification of song output. We find that neurons in the outflow nucleus of a specialized basal ganglia- thalamocortical circuit, the lateral magnocellular nucleus of the anterior nidopallium (LMAN), code for time in the motor gesture (song) both during singing directed to a female bird (performance) and when the bird sings alone (practice). Using mutual information to quantify the correlation between temporal sequences of spikes and time in song, we find that different symbols code for time in the two singing states. While isolated spikes code for particular parts of song during performance, extended strings of spiking and silence, particularly burst events, code for time in song during practice. This temporal coding during practice can be as precise as isolated spiking during performance to a female, supporting the hypothesis that neurons in LMAN actively sample motor space, guiding song modification at local instances in time. |
1501.04391 | Liane Gabora | Liane Gabora | How a Generation Was Misled About Natural Selection | 12 pages, Psychology Today (online).
http://www.psychologytoday.com/blog/mindbloggling. arXiv admin note:
substantial text overlap with arXiv:1309.2622 | null | null | null | q-bio.PE q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This article explains how natural selection works and how it has been
inappropriately applied to the description of cultural change. It proposes an
alternative evolutionary explanation for cultural evolution that describes it
in terms of communal exchange.
| [
{
"created": "Mon, 19 Jan 2015 05:30:38 GMT",
"version": "v1"
}
] | 2015-01-20 | [
[
"Gabora",
"Liane",
""
]
] | This article explains how natural selection works and how it has been inappropriately applied to the description of cultural change. It proposes an alternative evolutionary explanation for cultural evolution that describes it in terms of communal exchange. |
2205.09595 | Conor Heins | Conor Heins | Particular flows and attracting sets: A comment on "How particular is
the physics of the Free Energy Principle?" by Aguilera, Millidge, Tschantz
and Buckley | null | null | 10.1016/j.plrev.2022.06.003 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this commentary, I expand on the analysis of the recent article "How
particular is the physics of the Free Energy Principle?" by Aguilera et al. by
studying the flow fields of linear diffusions, and particularly the rotation of
their attracting sets in the presence of different types of solenoidal
coupling. This analysis sheds new light on previous claims made in the FEP
literature (and contested in the target article) that the internal dynamics of
stochastic systems can be cast performing a gradient flow on variational free
energy, and thus endowed with an inferential interpretation, i.e., as if
internal states are performing inference about states external to the system. I
express general agreement with the target article's statement that the marginal
flow of internal states does not point along variational free energy gradients
evaluated at the most likely internal state (i.e., the conditional mode).
However, in this commentary I focus on the flow of particular states (internal
and blanket states) and their variational free energy gradients, and show that
for a wide but restricted class of solenoidal couplings, the average flow of
these systems point along variational free energy gradients. This licenses a
different but perhaps stronger re-description of the flow of particular states
as performing inference, which importantly holds at arbitrary points in state
space, not just at the conditional modes.
| [
{
"created": "Thu, 19 May 2022 14:37:18 GMT",
"version": "v1"
}
] | 2022-07-20 | [
[
"Heins",
"Conor",
""
]
] | In this commentary, I expand on the analysis of the recent article "How particular is the physics of the Free Energy Principle?" by Aguilera et al. by studying the flow fields of linear diffusions, and particularly the rotation of their attracting sets in the presence of different types of solenoidal coupling. This analysis sheds new light on previous claims made in the FEP literature (and contested in the target article) that the internal dynamics of stochastic systems can be cast performing a gradient flow on variational free energy, and thus endowed with an inferential interpretation, i.e., as if internal states are performing inference about states external to the system. I express general agreement with the target article's statement that the marginal flow of internal states does not point along variational free energy gradients evaluated at the most likely internal state (i.e., the conditional mode). However, in this commentary I focus on the flow of particular states (internal and blanket states) and their variational free energy gradients, and show that for a wide but restricted class of solenoidal couplings, the average flow of these systems point along variational free energy gradients. This licenses a different but perhaps stronger re-description of the flow of particular states as performing inference, which importantly holds at arbitrary points in state space, not just at the conditional modes. |
2402.12205 | Hiroyuki Sato | Hiroyuki Sato, Keisuke Suzuki, Atsushi Hashizume, Ryoichi Hanazawa,
Masanao Sasaki, Akihiro Hirakawa, the Japanese Alzheimer's Disease
Neuroimaging Initiative, the Alzheimer's Disease Neuroimaging Initiative | Self-organized clustering, prediction, and superposition of long-term
cognitive decline from short-term individual cognitive test scores in
Alzheimer's disease | 37 pages, 6 figures | null | null | null | q-bio.QM q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Progressive cognitive decline spanning across decades is characteristic of
Alzheimer's disease (AD). Various predictive models have been designed to
realize its early onset and study the long-term trajectories of cognitive test
scores across populations of interest. Research efforts have been geared
towards superimposing patients' cognitive test scores with the long-term
trajectory denoting gradual cognitive decline, while considering the
heterogeneity of AD. Multiple trajectories representing cognitive assessment
for the long-term have been developed based on various parameters, highlighting
the importance of classifying several groups based on disease progression
patterns. In this study, a novel method capable of self-organized prediction,
classification, and the overlay of long-term cognitive trajectories based on
short-term individual data was developed, based on statistical and differential
equation modeling. We validated the predictive accuracy of the proposed method
for the long-term trajectory of cognitive test score results on two cohorts:
the Alzheimer's Disease Neuroimaging Initiative (ADNI) study and the Japanese
ADNI study. We also presented two practical illustrations of the simultaneous
evaluation of risk factor associated with both the onset and the longitudinal
progression of AD, and an innovative randomized controlled trial design for AD
that standardizes the heterogeneity of patients enrolled in a clinical trial.
These resources would improve the power of statistical hypothesis testing and
help evaluate the therapeutic effect. The application of predicting the
trajectory of longitudinal disease progression goes beyond AD, and is
especially relevant for progressive and neurodegenerative disorders.
| [
{
"created": "Mon, 19 Feb 2024 15:07:56 GMT",
"version": "v1"
}
] | 2024-02-20 | [
[
"Sato",
"Hiroyuki",
""
],
[
"Suzuki",
"Keisuke",
""
],
[
"Hashizume",
"Atsushi",
""
],
[
"Hanazawa",
"Ryoichi",
""
],
[
"Sasaki",
"Masanao",
""
],
[
"Hirakawa",
"Akihiro",
""
],
[
"Initiative",
"the Japanese Alzheimer's Disease Neuroimaging",
""
],
[
"Initiative",
"the Alzheimer's Disease Neuroimaging",
""
]
] | Progressive cognitive decline spanning across decades is characteristic of Alzheimer's disease (AD). Various predictive models have been designed to realize its early onset and study the long-term trajectories of cognitive test scores across populations of interest. Research efforts have been geared towards superimposing patients' cognitive test scores with the long-term trajectory denoting gradual cognitive decline, while considering the heterogeneity of AD. Multiple trajectories representing cognitive assessment for the long-term have been developed based on various parameters, highlighting the importance of classifying several groups based on disease progression patterns. In this study, a novel method capable of self-organized prediction, classification, and the overlay of long-term cognitive trajectories based on short-term individual data was developed, based on statistical and differential equation modeling. We validated the predictive accuracy of the proposed method for the long-term trajectory of cognitive test score results on two cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) study and the Japanese ADNI study. We also presented two practical illustrations of the simultaneous evaluation of risk factor associated with both the onset and the longitudinal progression of AD, and an innovative randomized controlled trial design for AD that standardizes the heterogeneity of patients enrolled in a clinical trial. These resources would improve the power of statistical hypothesis testing and help evaluate the therapeutic effect. The application of predicting the trajectory of longitudinal disease progression goes beyond AD, and is especially relevant for progressive and neurodegenerative disorders. |
1909.07288 | Patrice Loisel | Patrice Loisel (MISTEA), Guillerme Duvilli\'e (MAORE), Denis Barbeau,
Brigitte Charnomordic (MISTEA) | EvaSylv: A user-friendly software to evaluate forestry scenarii
including natural risk | null | null | null | null | q-bio.PE q-fin.RM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Forest management relies on the evaluation of silviculture practices. The
increase in natural risk due to climate change makes it necessary to consider
evaluation criteria that take natural risk into account. Risk integration in
existing software requires advanced programming skills.We propose a
user-friendly software to simulate even-aged and monospecific forest at the
stand level, in order to evaluate and optimize forest management. The software
gives the possibility to run management scenarii with or without considering
the impact of natural risk. The control variables are the dates and rates of
thinning and the cutting age.The risk model is based on a Poisson processus.
The Faustmann approach, including tree damage risk, is used to evaluate future
benefits, economic or ecosystem services. It relies on the calculation of
expected values, for which a dedicated mathematical development has been done.
The optimized criteria used to evaluate the various scenarii are the Faustmann
value and the Averaged yield value.We illustrate the approach and the software
on two case studies: economic optimization of a beech stand and carbon
sequestration optimization of a pine stand.Software interface makes it easy for
users to write their own (growth-tree damage-economic) models without advanced
programming skills. The possibility to run management scenarii with/without
considering the impact of natural risk may contribute improving silviculture
guidelines and adapting them to climate change. We propose future lines of
research and improvement.
| [
{
"created": "Thu, 12 Sep 2019 11:12:44 GMT",
"version": "v1"
}
] | 2019-09-17 | [
[
"Loisel",
"Patrice",
"",
"MISTEA"
],
[
"Duvillié",
"Guillerme",
"",
"MAORE"
],
[
"Barbeau",
"Denis",
"",
"MISTEA"
],
[
"Charnomordic",
"Brigitte",
"",
"MISTEA"
]
] | Forest management relies on the evaluation of silviculture practices. The increase in natural risk due to climate change makes it necessary to consider evaluation criteria that take natural risk into account. Risk integration in existing software requires advanced programming skills.We propose a user-friendly software to simulate even-aged and monospecific forest at the stand level, in order to evaluate and optimize forest management. The software gives the possibility to run management scenarii with or without considering the impact of natural risk. The control variables are the dates and rates of thinning and the cutting age.The risk model is based on a Poisson processus. The Faustmann approach, including tree damage risk, is used to evaluate future benefits, economic or ecosystem services. It relies on the calculation of expected values, for which a dedicated mathematical development has been done. The optimized criteria used to evaluate the various scenarii are the Faustmann value and the Averaged yield value.We illustrate the approach and the software on two case studies: economic optimization of a beech stand and carbon sequestration optimization of a pine stand.Software interface makes it easy for users to write their own (growth-tree damage-economic) models without advanced programming skills. The possibility to run management scenarii with/without considering the impact of natural risk may contribute improving silviculture guidelines and adapting them to climate change. We propose future lines of research and improvement. |
2007.00031 | Sacha van Albada | Sacha Jennifer van Albada, Aitor Morales-Gregorio, Timo Dickscheid,
Alexandros Goulas, Rembrandt Bakker, Sebastian Bludau, G\"unther Palm,
Claus-Christian Hilgetag, Markus Diesmann | Bringing Anatomical Information into Neuronal Network Models | null | null | 10.1007/978-3-030-89439-9_9 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | For constructing neuronal network models computational neuroscientists have
access to wide-ranging anatomical data that nevertheless tend to cover only a
fraction of the parameters to be determined. Finding and interpreting the most
relevant data, estimating missing values, and combining the data and estimates
from various sources into a coherent whole is a daunting task. With this
chapter we aim to provide guidance to modelers by describing the main types of
anatomical data that may be useful for informing neuronal network models. We
further discuss aspects of the underlying experimental techniques relevant to
the interpretation of the data, list particularly comprehensive data sets, and
describe methods for filling in the gaps in the experimental data. Such methods
of `predictive connectomics' estimate connectivity where the data are lacking
based on statistical relationships with known quantities. It is instructive,
and in certain cases necessary, to use organizational principles that link the
plethora of data within a unifying framework where regularities of brain
structure can be exploited to inform computational models. In addition, we
touch upon the most prominent features of brain organization that are likely to
influence predicted neuronal network dynamics, with a focus on the mammalian
cerebral cortex. Given the still existing need for modelers to navigate a
complex data landscape full of holes and stumbling blocks, it is vital that the
field of neuroanatomy is moving toward increasingly systematic data collection,
representation, and publication.
| [
{
"created": "Tue, 30 Jun 2020 18:02:17 GMT",
"version": "v1"
},
{
"created": "Tue, 11 Aug 2020 10:19:09 GMT",
"version": "v2"
}
] | 2022-04-29 | [
[
"van Albada",
"Sacha Jennifer",
""
],
[
"Morales-Gregorio",
"Aitor",
""
],
[
"Dickscheid",
"Timo",
""
],
[
"Goulas",
"Alexandros",
""
],
[
"Bakker",
"Rembrandt",
""
],
[
"Bludau",
"Sebastian",
""
],
[
"Palm",
"Günther",
""
],
[
"Hilgetag",
"Claus-Christian",
""
],
[
"Diesmann",
"Markus",
""
]
] | For constructing neuronal network models computational neuroscientists have access to wide-ranging anatomical data that nevertheless tend to cover only a fraction of the parameters to be determined. Finding and interpreting the most relevant data, estimating missing values, and combining the data and estimates from various sources into a coherent whole is a daunting task. With this chapter we aim to provide guidance to modelers by describing the main types of anatomical data that may be useful for informing neuronal network models. We further discuss aspects of the underlying experimental techniques relevant to the interpretation of the data, list particularly comprehensive data sets, and describe methods for filling in the gaps in the experimental data. Such methods of `predictive connectomics' estimate connectivity where the data are lacking based on statistical relationships with known quantities. It is instructive, and in certain cases necessary, to use organizational principles that link the plethora of data within a unifying framework where regularities of brain structure can be exploited to inform computational models. In addition, we touch upon the most prominent features of brain organization that are likely to influence predicted neuronal network dynamics, with a focus on the mammalian cerebral cortex. Given the still existing need for modelers to navigate a complex data landscape full of holes and stumbling blocks, it is vital that the field of neuroanatomy is moving toward increasingly systematic data collection, representation, and publication. |
1903.09103 | Diederik Aerts | Diederik Aerts, Jonito Aerts Argu\"elles, Lester Beltran, Suzette
Geriente, Massimiliano Sassoli de Bianchi, Sandro Sozzo and Tomas Veloz | Quantum entanglement in physical and cognitive systems: a conceptual
analysis and a general representation | null | The European Physical Journal Plus 134, 493 (2019) | 10.1140/epjp/i2019-12987-0 | null | q-bio.NC quant-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We provide a general description of the phenomenon of entanglement in
bipartite systems, as it manifests in micro and macro physical systems, as well
as in human cognitive processes. We do so by observing that when genuine
coincidence measurements are considered, the violation of the 'marginal laws',
in addition to the Bell-CHSH inequality, is also to be expected. The situation
can be described in the quantum formalism by considering the presence of
entanglement not only at the level of the states, but also at the level of the
measurements. However, at the "local'" level of a specific joint measurement, a
description where entanglement is only incorporated in the state remains always
possible, by adopting a fine-tuned tensor product representation. But
contextual tensor product representations should only be considered when there
are good reasons to describe the outcome-states as (non-entangled) product
states. This will not in general be true, hence, the entangement resource will
have to generally be allocated both in the states and in the measurements. In
view of the numerous violations of the marginal laws observed in physics'
laboratories, it remains unclear to date if entanglement in micro-physical
systems is to be understood only as an 'entanglement of the states', or also as
an 'entanglement of the measurements'. But even if measurements would also be
entangled, the corresponding violation of the marginal laws (no-signaling
conditions) would not for this imply that a superluminal communication would be
possible.
| [
{
"created": "Thu, 21 Mar 2019 16:38:49 GMT",
"version": "v1"
}
] | 2023-02-27 | [
[
"Aerts",
"Diederik",
""
],
[
"Arguëlles",
"Jonito Aerts",
""
],
[
"Beltran",
"Lester",
""
],
[
"Geriente",
"Suzette",
""
],
[
"de Bianchi",
"Massimiliano Sassoli",
""
],
[
"Sozzo",
"Sandro",
""
],
[
"Veloz",
"Tomas",
""
]
] | We provide a general description of the phenomenon of entanglement in bipartite systems, as it manifests in micro and macro physical systems, as well as in human cognitive processes. We do so by observing that when genuine coincidence measurements are considered, the violation of the 'marginal laws', in addition to the Bell-CHSH inequality, is also to be expected. The situation can be described in the quantum formalism by considering the presence of entanglement not only at the level of the states, but also at the level of the measurements. However, at the "local'" level of a specific joint measurement, a description where entanglement is only incorporated in the state remains always possible, by adopting a fine-tuned tensor product representation. But contextual tensor product representations should only be considered when there are good reasons to describe the outcome-states as (non-entangled) product states. This will not in general be true, hence, the entangement resource will have to generally be allocated both in the states and in the measurements. In view of the numerous violations of the marginal laws observed in physics' laboratories, it remains unclear to date if entanglement in micro-physical systems is to be understood only as an 'entanglement of the states', or also as an 'entanglement of the measurements'. But even if measurements would also be entangled, the corresponding violation of the marginal laws (no-signaling conditions) would not for this imply that a superluminal communication would be possible. |
1408.0247 | Rebekah Rogers | Rebekah L. Rogers, Ling Shao, Jaleal S. Sanjak, Peter Andolfatto, and
Kevin R. Thornton | Revised Annotations, Sex-Biased Expression, and Lineage-Specific Genes
in the Drosophila melanogaster group | Revised manuscript, also available online preprint at G3: Genes,
Genomes, Genetics. Gene models, ortholog calls, and tissue specific
expression results are available at http://github.com/ThorntonLab/GFF or the
UCSC browser on the Thornton Lab public track hub at http://genome.ucsc.edu | null | 10.1534/g3.114.013532 | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Here, we provide revised gene models for D. ananassae, D. yakuba, and D.
simulans, which include UTRs and empirically verified intron-exon boundaries,
as well as ortholog groups identified using a fuzzy reciprocal-best-hit blast
comparison. Using these revised annotations, we perform differential expression
testing using the cufflinks suite to provide a broad overview of differential
expression between reproductive tissues and the carcass. We identify thousands
of genes that are differentially expressed across tissues in D. yakuba and D.
simulans, with roughly 60% agreement in expression patterns of orthologs in D.
yakuba and D. simulans. We identify several cases of putative polycistronic
transcripts, pointing to a combination of transcriptional read-through in the
genome as well as putative gene fusion and fission events across taxa. We
furthermore identify hundreds of lineage specific genes in each species with no
blast hits among transcripts of any other Drosophila species, which are
candidates for neofunctionalized proteins and a potential source of genetic
novelty.
| [
{
"created": "Fri, 1 Aug 2014 17:59:53 GMT",
"version": "v1"
},
{
"created": "Wed, 1 Oct 2014 22:24:31 GMT",
"version": "v2"
}
] | 2014-10-03 | [
[
"Rogers",
"Rebekah L.",
""
],
[
"Shao",
"Ling",
""
],
[
"Sanjak",
"Jaleal S.",
""
],
[
"Andolfatto",
"Peter",
""
],
[
"Thornton",
"Kevin R.",
""
]
] | Here, we provide revised gene models for D. ananassae, D. yakuba, and D. simulans, which include UTRs and empirically verified intron-exon boundaries, as well as ortholog groups identified using a fuzzy reciprocal-best-hit blast comparison. Using these revised annotations, we perform differential expression testing using the cufflinks suite to provide a broad overview of differential expression between reproductive tissues and the carcass. We identify thousands of genes that are differentially expressed across tissues in D. yakuba and D. simulans, with roughly 60% agreement in expression patterns of orthologs in D. yakuba and D. simulans. We identify several cases of putative polycistronic transcripts, pointing to a combination of transcriptional read-through in the genome as well as putative gene fusion and fission events across taxa. We furthermore identify hundreds of lineage specific genes in each species with no blast hits among transcripts of any other Drosophila species, which are candidates for neofunctionalized proteins and a potential source of genetic novelty. |
2107.08855 | Carsten Baldauf | Xiaojuan Hu, Maja-Olivia Lenz-Himmer, Carsten Baldauf | Better force fields start with better data -- A data set of cation
dipeptide interactions | submitted manuscript | null | null | null | q-bio.BM physics.atm-clus physics.chem-ph | http://creativecommons.org/licenses/by-nc-sa/4.0/ | We present a data set from a first-principles study of amino-methylated and
acetylated (capped) dipeptides of the 20 proteinogenic amino acids - including
alternative possible side chain protonation states and their interactions with
selected divalent cations (Ca$^{2+}$, Mg$^{2+}$ and Ba$^{2+}$). The data covers
21,909 stationary points on the respective potential-energy surfaces in a wide
relative energy range of up to 4 eV (390 kJ/mol). Relevant properties of
interest, like partial charges, were derived for the conformers. The motivation
was to provide a solid data basis for force field parameterization and further
applications like machine learning or benchmarking. In particular the process
of creating all this data on the same first-principles footing, i.e.
density-functional theory calculations employing the generalized gradient
approximation with a van der Waals correction, makes this data suitable for
data-driven force field development. To make the data accessible across domain
borders and to machines, we formalized the metadata in an ontology.
| [
{
"created": "Mon, 19 Jul 2021 13:13:31 GMT",
"version": "v1"
}
] | 2021-07-20 | [
[
"Hu",
"Xiaojuan",
""
],
[
"Lenz-Himmer",
"Maja-Olivia",
""
],
[
"Baldauf",
"Carsten",
""
]
] | We present a data set from a first-principles study of amino-methylated and acetylated (capped) dipeptides of the 20 proteinogenic amino acids - including alternative possible side chain protonation states and their interactions with selected divalent cations (Ca$^{2+}$, Mg$^{2+}$ and Ba$^{2+}$). The data covers 21,909 stationary points on the respective potential-energy surfaces in a wide relative energy range of up to 4 eV (390 kJ/mol). Relevant properties of interest, like partial charges, were derived for the conformers. The motivation was to provide a solid data basis for force field parameterization and further applications like machine learning or benchmarking. In particular the process of creating all this data on the same first-principles footing, i.e. density-functional theory calculations employing the generalized gradient approximation with a van der Waals correction, makes this data suitable for data-driven force field development. To make the data accessible across domain borders and to machines, we formalized the metadata in an ontology. |
1310.0498 | Jorge Pe\~na | Jorge Pe\~na, Laurent Lehmann, Georg N\"oldeke | Gains from switching and evolutionary stability in multi-player matrix
games | 5 figures | null | null | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we unify, simplify, and extend previous work on the
evolutionary dynamics of symmetric $N$-player matrix games with two pure
strategies. In such games, gains from switching strategies depend, in general,
on how many other individuals in the group play a given strategy. As a
consequence, the gain function determining the gradient of selection can be a
polynomial of degree $N-1$. In order to deal with the intricacy of the
resulting evolutionary dynamics, we make use of the theory of polynomials in
Bernstein form. This theory implies a tight link between the sign pattern of
the gains from switching on the one hand and the number and stability
properties of the rest points of the replicator dynamics on the other hand.
While this relationship is a general one, it is most informative if gains from
switching have at most two sign changes, as it is the case for most
multi-player matrix games considered in the literature. We demonstrate that
previous results for public goods games are easily recovered and extended using
this observation. Further examples illustrate how focusing on the sign pattern
of the gains from switching obviates the need for a more involved analysis.
| [
{
"created": "Tue, 1 Oct 2013 21:41:16 GMT",
"version": "v1"
}
] | 2013-10-03 | [
[
"Peña",
"Jorge",
""
],
[
"Lehmann",
"Laurent",
""
],
[
"Nöldeke",
"Georg",
""
]
] | In this paper we unify, simplify, and extend previous work on the evolutionary dynamics of symmetric $N$-player matrix games with two pure strategies. In such games, gains from switching strategies depend, in general, on how many other individuals in the group play a given strategy. As a consequence, the gain function determining the gradient of selection can be a polynomial of degree $N-1$. In order to deal with the intricacy of the resulting evolutionary dynamics, we make use of the theory of polynomials in Bernstein form. This theory implies a tight link between the sign pattern of the gains from switching on the one hand and the number and stability properties of the rest points of the replicator dynamics on the other hand. While this relationship is a general one, it is most informative if gains from switching have at most two sign changes, as it is the case for most multi-player matrix games considered in the literature. We demonstrate that previous results for public goods games are easily recovered and extended using this observation. Further examples illustrate how focusing on the sign pattern of the gains from switching obviates the need for a more involved analysis. |
1303.4303 | Paulo Murilo Castro de Oliveira | Paulo Murilo Castro de Oliveira | Dynamic Ising Model: Reconstruction of Evolutionary Trees | 8 pages, 4 figures | J. Phys. A: Math. Theor. 46 (2013) 365102 | 10.1088/1751-8113/46/36/365102 | null | q-bio.QM q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | An evolutionary tree is a cascade of bifurcations starting from a single
common root, generating a growing set of daughter species as time goes by.
Species here is a general denomination for biological species, spoken languages
or any other entity evolving through heredity. From the N currently alive
species within a clade, distances are measured through pairwise comparisons
made by geneticists, linguists, etc. The larger is such a distance for a pair
of species, the older is their last common ancestor. The aim is to reconstruct
the past unknown bifurcations, i.e. the whole clade, from the knowledge of the
N(N-1)/2 quoted distances taken for granted. A mechanical method is presented,
and its applicability discussed.
| [
{
"created": "Mon, 18 Mar 2013 16:11:05 GMT",
"version": "v1"
},
{
"created": "Fri, 23 Aug 2013 13:53:57 GMT",
"version": "v2"
}
] | 2013-08-26 | [
[
"de Oliveira",
"Paulo Murilo Castro",
""
]
] | An evolutionary tree is a cascade of bifurcations starting from a single common root, generating a growing set of daughter species as time goes by. Species here is a general denomination for biological species, spoken languages or any other entity evolving through heredity. From the N currently alive species within a clade, distances are measured through pairwise comparisons made by geneticists, linguists, etc. The larger is such a distance for a pair of species, the older is their last common ancestor. The aim is to reconstruct the past unknown bifurcations, i.e. the whole clade, from the knowledge of the N(N-1)/2 quoted distances taken for granted. A mechanical method is presented, and its applicability discussed. |
1711.01177 | Jeremie Kim | Jeremie S. Kim, Damla Senol Cali, Hongyi Xin, Donghyuk Lee, Saugata
Ghose, Mohammed Alser, Hasan Hassan, Oguz Ergin, Can Alkan and Onur Mutlu | GRIM-Filter: Fast Seed Location Filtering in DNA Read Mapping Using
Processing-in-Memory Technologies | arXiv admin note: text overlap with arXiv:1708.04329 | BMC Genomics, 19 (Suppl 2):89, 2018 | 10.1186/s12864-018-4460-0 | null | q-bio.GN cs.CE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Motivation: Seed location filtering is critical in DNA read mapping, a
process where billions of DNA fragments (reads) sampled from a donor are mapped
onto a reference genome to identify genomic variants of the donor.
State-of-the-art read mappers 1) quickly generate possible mapping locations
for seeds (i.e., smaller segments) within each read, 2) extract reference
sequences at each of the mapping locations, and 3) check similarity between
each read and its associated reference sequences with a
computationally-expensive algorithm (i.e., sequence alignment) to determine the
origin of the read. A seed location filter comes into play before alignment,
discarding seed locations that alignment would deem a poor match. The ideal
seed location filter would discard all poor match locations prior to alignment
such that there is no wasted computation on unnecessary alignments.
Results: We propose a novel seed location filtering algorithm, GRIM-Filter,
optimized to exploit 3D-stacked memory systems that integrate computation
within a logic layer stacked under memory layers, to perform
processing-in-memory (PIM). GRIM-Filter quickly filters seed locations by 1)
introducing a new representation of coarse-grained segments of the reference
genome, and 2) using massively-parallel in-memory operations to identify read
presence within each coarse-grained segment. Our evaluations show that for a
sequence alignment error tolerance of 0.05, GRIM-Filter 1) reduces the false
negative rate of filtering by 5.59x--6.41x, and 2) provides an end-to-end read
mapper speedup of 1.81x--3.65x, compared to a state-of-the-art read mapper
employing the best previous seed location filtering algorithm.
Availability: The code is available online at:
https://github.com/CMU-SAFARI/GRIM
| [
{
"created": "Thu, 2 Nov 2017 16:03:46 GMT",
"version": "v1"
}
] | 2020-04-21 | [
[
"Kim",
"Jeremie S.",
""
],
[
"Cali",
"Damla Senol",
""
],
[
"Xin",
"Hongyi",
""
],
[
"Lee",
"Donghyuk",
""
],
[
"Ghose",
"Saugata",
""
],
[
"Alser",
"Mohammed",
""
],
[
"Hassan",
"Hasan",
""
],
[
"Ergin",
"Oguz",
""
],
[
"Alkan",
"Can",
""
],
[
"Mutlu",
"Onur",
""
]
] | Motivation: Seed location filtering is critical in DNA read mapping, a process where billions of DNA fragments (reads) sampled from a donor are mapped onto a reference genome to identify genomic variants of the donor. State-of-the-art read mappers 1) quickly generate possible mapping locations for seeds (i.e., smaller segments) within each read, 2) extract reference sequences at each of the mapping locations, and 3) check similarity between each read and its associated reference sequences with a computationally-expensive algorithm (i.e., sequence alignment) to determine the origin of the read. A seed location filter comes into play before alignment, discarding seed locations that alignment would deem a poor match. The ideal seed location filter would discard all poor match locations prior to alignment such that there is no wasted computation on unnecessary alignments. Results: We propose a novel seed location filtering algorithm, GRIM-Filter, optimized to exploit 3D-stacked memory systems that integrate computation within a logic layer stacked under memory layers, to perform processing-in-memory (PIM). GRIM-Filter quickly filters seed locations by 1) introducing a new representation of coarse-grained segments of the reference genome, and 2) using massively-parallel in-memory operations to identify read presence within each coarse-grained segment. Our evaluations show that for a sequence alignment error tolerance of 0.05, GRIM-Filter 1) reduces the false negative rate of filtering by 5.59x--6.41x, and 2) provides an end-to-end read mapper speedup of 1.81x--3.65x, compared to a state-of-the-art read mapper employing the best previous seed location filtering algorithm. Availability: The code is available online at: https://github.com/CMU-SAFARI/GRIM |
2010.09441 | Gholamreza Jafari | Z. Moradimanesh (1), R. Khosrowabadi (1), M. Eshaghi Gordji (2), G. R.
Jafari (3, 1 and 4) ((1) Institute for Cognitive and Brain Sciences, Shahid
Beheshti University, (2) Department of Mathematics, Semnan University, (3)
Department of Physics, Shahid Beheshti University, (4) Department of Network
and Data Science, Central European University) | Altered structural balance of resting-state networks in autism | Published version | Scientific reports 11.1 (2021): 1-16 | 10.1038/s41598-020-80330-0 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | What makes a network complex, in addition to its size, is the interconnected
interactions between elements, disruption of which inevitably results in
dysfunction. Likewise, the brain networks' complexity arises from interactions
beyond pair connections, as it is simplistic to assume that in complex networks
state of a link is independently determined only according to its two
constituting nodes. This is particularly of note in genetically complex brain
impairments, such as the autism spectrum disorder (ASD), which has a surprising
heterogeneity in manifestations with no clear-cut neuropathology. Accordingly,
structural balance theory (SBT) affirms that in real-world signed networks, a
link is remarkably influenced by each of its two nodes' interactions with the
third node within a triadic interrelationship. Thus, it is plausible to ask
whether ASD is associated with altered structural balance resulting from
atypical triadic interactions. In other words, it is the abnormal interplay of
positive and negative interactions that matters in ASD, besides and beyond hypo
(hyper) pair connectivity. To address this question, we explore triadic
interactions based on SBT in the weighted signed resting-state functional
magnetic resonance imaging networks of participants with ASD relative to
healthy controls (CON). We demonstrate that balanced triads are overrepresented
in the ASD and CON networks while unbalanced triads are underrepresented,
providing first-time empirical evidence for the strong notion of structural
balance on the brain networks. We further analyze the frequency and energy
distributions of different triads and suggest an alternative description for
the reduced functional integration and segregation in the ASD brain networks.
Moreover, results reveal that the scale of change in the whole-brain networks'
energy is more narrow in the ASD networks during development.
| [
{
"created": "Tue, 6 Oct 2020 16:28:35 GMT",
"version": "v1"
},
{
"created": "Wed, 21 Oct 2020 13:14:42 GMT",
"version": "v2"
},
{
"created": "Thu, 14 Oct 2021 10:43:47 GMT",
"version": "v3"
}
] | 2022-04-19 | [
[
"Moradimanesh",
"Z.",
"",
"3, 1 and 4"
],
[
"Khosrowabadi",
"R.",
"",
"3, 1 and 4"
],
[
"Gordji",
"M. Eshaghi",
"",
"3, 1 and 4"
],
[
"Jafari",
"G. R.",
"",
"3, 1 and 4"
]
] | What makes a network complex, in addition to its size, is the interconnected interactions between elements, disruption of which inevitably results in dysfunction. Likewise, the brain networks' complexity arises from interactions beyond pair connections, as it is simplistic to assume that in complex networks state of a link is independently determined only according to its two constituting nodes. This is particularly of note in genetically complex brain impairments, such as the autism spectrum disorder (ASD), which has a surprising heterogeneity in manifestations with no clear-cut neuropathology. Accordingly, structural balance theory (SBT) affirms that in real-world signed networks, a link is remarkably influenced by each of its two nodes' interactions with the third node within a triadic interrelationship. Thus, it is plausible to ask whether ASD is associated with altered structural balance resulting from atypical triadic interactions. In other words, it is the abnormal interplay of positive and negative interactions that matters in ASD, besides and beyond hypo (hyper) pair connectivity. To address this question, we explore triadic interactions based on SBT in the weighted signed resting-state functional magnetic resonance imaging networks of participants with ASD relative to healthy controls (CON). We demonstrate that balanced triads are overrepresented in the ASD and CON networks while unbalanced triads are underrepresented, providing first-time empirical evidence for the strong notion of structural balance on the brain networks. We further analyze the frequency and energy distributions of different triads and suggest an alternative description for the reduced functional integration and segregation in the ASD brain networks. Moreover, results reveal that the scale of change in the whole-brain networks' energy is more narrow in the ASD networks during development. |
2310.05217 | Rong Zhang | Rong Zhang and Rongqing Yuan and Boxue Tian | PointGAT: A quantum chemical property prediction model integrating graph
attention and 3D geometry | 38 pages, 12 figures | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Predicting quantum chemical properties is a fundamental challenge for
computational chemistry. While the development of graph neural networks has
advanced molecular representation learning and property prediction, their
performance could be further enhanced by incorporating 3D structural geometry
into 2D molecular graph representation. In this study, we introduce the
PointGAT model for quantum molecular property prediction, which integrates 3D
molecular coordinates with graph-attention modeling. Comparison with other
current models in molecular prediction tasks showed that PointGAT could provide
higher predictive accuracy in various benchmark datasets from MoleculeNet,
including ESOL, FreeSolv, Lipop, HIV, and 10 out of 12 tasks of the QM9
dataset. To further examine PointGAT prediction of quantum mechanical (QM)
energies, we constructed a C10 dataset comprising 11,841 charged and chiral
carbocation intermediates with QM energies calculated at the
DM21/6-31G*//B3LYP/6-31G* levels. Notably, PointGAT achieved an R2 value of
0.950 and an MAE of 1.616 kcal/mol, outperforming other models. Additional
ablation studies indicated that incorporating molecular geometry into the model
resulted in markedly higher predictive accuracy, reducing the MAE value from
1.802 kcal/mol to 1.616 kcal/mol. Moreover, visualization of PointGAT atomic
attention weights suggested its predictions were interpretable. Findings in
this study support the application of PointGAT as a powerful and versatile tool
for quantum chemical property prediction that can facilitate high-accuracy
modeling for fundamental exploration of chemical space as well as drug design
and molecular engineering.
| [
{
"created": "Sun, 8 Oct 2023 16:25:32 GMT",
"version": "v1"
}
] | 2023-10-10 | [
[
"Zhang",
"Rong",
""
],
[
"Yuan",
"Rongqing",
""
],
[
"Tian",
"Boxue",
""
]
] | Predicting quantum chemical properties is a fundamental challenge for computational chemistry. While the development of graph neural networks has advanced molecular representation learning and property prediction, their performance could be further enhanced by incorporating 3D structural geometry into 2D molecular graph representation. In this study, we introduce the PointGAT model for quantum molecular property prediction, which integrates 3D molecular coordinates with graph-attention modeling. Comparison with other current models in molecular prediction tasks showed that PointGAT could provide higher predictive accuracy in various benchmark datasets from MoleculeNet, including ESOL, FreeSolv, Lipop, HIV, and 10 out of 12 tasks of the QM9 dataset. To further examine PointGAT prediction of quantum mechanical (QM) energies, we constructed a C10 dataset comprising 11,841 charged and chiral carbocation intermediates with QM energies calculated at the DM21/6-31G*//B3LYP/6-31G* levels. Notably, PointGAT achieved an R2 value of 0.950 and an MAE of 1.616 kcal/mol, outperforming other models. Additional ablation studies indicated that incorporating molecular geometry into the model resulted in markedly higher predictive accuracy, reducing the MAE value from 1.802 kcal/mol to 1.616 kcal/mol. Moreover, visualization of PointGAT atomic attention weights suggested its predictions were interpretable. Findings in this study support the application of PointGAT as a powerful and versatile tool for quantum chemical property prediction that can facilitate high-accuracy modeling for fundamental exploration of chemical space as well as drug design and molecular engineering. |
1310.3001 | Liane Gabora | Kirsty Kitto, Peter Bruza, and Liane Gabora | A Quantum Information Retrieval Approach to Memory | 8 pages; 2 figures | (2012). Proceedings of the International Joint Conference on
Neural Networks, (pp. 932-939). June 10-15, Brisbane, Australia, IEEE
Computational Intelligence Society | 10.1109/IJCNN.2012.6252492 | null | q-bio.NC quant-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | As computers approach the physical limits of information storable in memory,
new methods will be needed to further improve information storage and
retrieval. We propose a quantum inspired vector based approach, which offers a
contextually dependent mapping from the subsymbolic to the symbolic
representations of information. If implemented computationally, this approach
would provide exceptionally high density of information storage, without the
traditionally required physical increase in storage capacity. The approach is
inspired by the structure of human memory and incorporates elements of
Gardenfors' Conceptual Space approach and Humphreys et al.'s matrix model of
memory.
| [
{
"created": "Fri, 11 Oct 2013 02:15:38 GMT",
"version": "v1"
}
] | 2016-11-17 | [
[
"Kitto",
"Kirsty",
""
],
[
"Bruza",
"Peter",
""
],
[
"Gabora",
"Liane",
""
]
] | As computers approach the physical limits of information storable in memory, new methods will be needed to further improve information storage and retrieval. We propose a quantum inspired vector based approach, which offers a contextually dependent mapping from the subsymbolic to the symbolic representations of information. If implemented computationally, this approach would provide exceptionally high density of information storage, without the traditionally required physical increase in storage capacity. The approach is inspired by the structure of human memory and incorporates elements of Gardenfors' Conceptual Space approach and Humphreys et al.'s matrix model of memory. |
2306.16989 | Jacob Luber | Michael Robben, Amir Hajighasemi, Mohammad Sadegh Nasr, Jai Prakesh
Veerla, Anne M. Alsup, Biraaj Rout, Helen H. Shang, Kelli Fowlds, Parisa
Boodaghi Malidarreh, Paul Koomey, MD Jillur Rahman Saurav, Jacob M. Luber | The State of Applying Artificial Intelligence to Tissue Imaging for
Cancer Research and Early Detection | null | F1000Research 2023, 12:1436 | 10.12688/f1000research.139210.1 | null | q-bio.TO cs.CV eess.IV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Artificial intelligence represents a new frontier in human medicine that
could save more lives and reduce the costs, thereby increasing accessibility.
As a consequence, the rate of advancement of AI in cancer medical imaging and
more particularly tissue pathology has exploded, opening it to ethical and
technical questions that could impede its adoption into existing systems. In
order to chart the path of AI in its application to cancer tissue imaging, we
review current work and identify how it can improve cancer pathology
diagnostics and research. In this review, we identify 5 core tasks that models
are developed for, including regression, classification, segmentation,
generation, and compression tasks. We address the benefits and challenges that
such methods face, and how they can be adapted for use in cancer prevention and
treatment. The studies looked at in this paper represent the beginning of this
field and future experiments will build on the foundations that we highlight.
| [
{
"created": "Thu, 29 Jun 2023 14:47:03 GMT",
"version": "v1"
}
] | 2024-01-08 | [
[
"Robben",
"Michael",
""
],
[
"Hajighasemi",
"Amir",
""
],
[
"Nasr",
"Mohammad Sadegh",
""
],
[
"Veerla",
"Jai Prakesh",
""
],
[
"Alsup",
"Anne M.",
""
],
[
"Rout",
"Biraaj",
""
],
[
"Shang",
"Helen H.",
""
],
[
"Fowlds",
"Kelli",
""
],
[
"Malidarreh",
"Parisa Boodaghi",
""
],
[
"Koomey",
"Paul",
""
],
[
"Saurav",
"MD Jillur Rahman",
""
],
[
"Luber",
"Jacob M.",
""
]
] | Artificial intelligence represents a new frontier in human medicine that could save more lives and reduce the costs, thereby increasing accessibility. As a consequence, the rate of advancement of AI in cancer medical imaging and more particularly tissue pathology has exploded, opening it to ethical and technical questions that could impede its adoption into existing systems. In order to chart the path of AI in its application to cancer tissue imaging, we review current work and identify how it can improve cancer pathology diagnostics and research. In this review, we identify 5 core tasks that models are developed for, including regression, classification, segmentation, generation, and compression tasks. We address the benefits and challenges that such methods face, and how they can be adapted for use in cancer prevention and treatment. The studies looked at in this paper represent the beginning of this field and future experiments will build on the foundations that we highlight. |
2202.12300 | St\'ephanie Abo | St\'ephanie M. C. Abo, Jos\'e A. Carrillo, Anita T. Layton | Can the clocks tick together despite the noise? Stochastic simulations
and analysis | null | null | null | null | q-bio.NC cs.NA math.DS math.NA math.PR | http://creativecommons.org/licenses/by-nc-nd/4.0/ | The suprachiasmatic nucleus (SCN), also known as the circadian master clock,
consists of a large population of oscillator neurons. Together, these neurons
produce a coherent signal that drives the body's circadian rhythms. What
properties of the cell-to-cell communication allow the synchronization of these
neurons, despite a wide range of environmental challenges such as fluctuations
in photoperiods? To answer that question, we present a mean-field description
of globally coupled neurons modeled as Goodwin oscillators with standard
Gaussian noise. Provided that the initial conditions of all neurons are
independent and identically distributed, any finite number of neurons becomes
independent and has the same probability distribution in the mean-field limit,
a phenomenon called propagation of chaos. This probability distribution is a
solution to a Vlasov-Fokker-Planck type equation, which can be obtained from
the stochastic particle model. We study, using the macroscopic description, how
the interaction between external noise and intercellular coupling affects the
dynamics of the collective rhythm, and we provide a numerical description of
the bifurcations resulting from the noise-induced transitions. Our numerical
simulations show a noise-induced rhythm generation at low noise intensities,
while the SCN clock is arrhythmic in the high noise setting. Notably, coupling
induces resonance-like behavior at low noise intensities, and varying coupling
strength can cause period locking and variance dissipation even in the presence
of noise.
| [
{
"created": "Thu, 24 Feb 2022 15:56:53 GMT",
"version": "v1"
},
{
"created": "Tue, 3 Jan 2023 10:58:40 GMT",
"version": "v2"
}
] | 2023-01-04 | [
[
"Abo",
"Stéphanie M. C.",
""
],
[
"Carrillo",
"José A.",
""
],
[
"Layton",
"Anita T.",
""
]
] | The suprachiasmatic nucleus (SCN), also known as the circadian master clock, consists of a large population of oscillator neurons. Together, these neurons produce a coherent signal that drives the body's circadian rhythms. What properties of the cell-to-cell communication allow the synchronization of these neurons, despite a wide range of environmental challenges such as fluctuations in photoperiods? To answer that question, we present a mean-field description of globally coupled neurons modeled as Goodwin oscillators with standard Gaussian noise. Provided that the initial conditions of all neurons are independent and identically distributed, any finite number of neurons becomes independent and has the same probability distribution in the mean-field limit, a phenomenon called propagation of chaos. This probability distribution is a solution to a Vlasov-Fokker-Planck type equation, which can be obtained from the stochastic particle model. We study, using the macroscopic description, how the interaction between external noise and intercellular coupling affects the dynamics of the collective rhythm, and we provide a numerical description of the bifurcations resulting from the noise-induced transitions. Our numerical simulations show a noise-induced rhythm generation at low noise intensities, while the SCN clock is arrhythmic in the high noise setting. Notably, coupling induces resonance-like behavior at low noise intensities, and varying coupling strength can cause period locking and variance dissipation even in the presence of noise. |
2010.09085 | Grzegorz Rzadkowski | Grzegorz Rzadkowski | Logistic wavelets and logistic function: An application to model the
spread of SARS-CoV-2 virus infections | 11 pages, 5 figures | null | 10.3390/app11178147 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In the present paper, we model the cumulative number of persons reported to
be infected by the SARS-CoV-2 virus, in a country or a region, by a sum of
logistic functions. For a given logistic function, using Eulerian numbers, we
find the zeros of its successive derivatives and their relationship with the
saturation level of this function. In a given time series, having potentially
the logistic trend, we use its second differences to determine points
corresponding to these zeros. To estimate the parameters of the approximating
logistic function, we define and use logistic wavelets. Then we apply the
theory to the cases of SARS-CoV-2 infections in the United States and the
United Kingdom.
| [
{
"created": "Sun, 18 Oct 2020 19:51:03 GMT",
"version": "v1"
}
] | 2023-07-07 | [
[
"Rzadkowski",
"Grzegorz",
""
]
] | In the present paper, we model the cumulative number of persons reported to be infected by the SARS-CoV-2 virus, in a country or a region, by a sum of logistic functions. For a given logistic function, using Eulerian numbers, we find the zeros of its successive derivatives and their relationship with the saturation level of this function. In a given time series, having potentially the logistic trend, we use its second differences to determine points corresponding to these zeros. To estimate the parameters of the approximating logistic function, we define and use logistic wavelets. Then we apply the theory to the cases of SARS-CoV-2 infections in the United States and the United Kingdom. |
2312.04064 | Pascal Notin | Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer,
Yarin Gal, Patrick Schwab | DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment
Design | null | International Conference on Machine Learning, 2023 | null | null | q-bio.QM cs.LG stat.ME | http://creativecommons.org/licenses/by-nc-nd/4.0/ | The discovery of therapeutics to treat genetically-driven pathologies relies
on identifying genes involved in the underlying disease mechanisms. Existing
approaches search over the billions of potential interventions to maximize the
expected influence on the target phenotype. However, to reduce the risk of
failure in future stages of trials, practical experiment design aims to find a
set of interventions that maximally change a target phenotype via diverse
mechanisms. We propose DiscoBAX, a sample-efficient method for maximizing the
rate of significant discoveries per experiment while simultaneously probing for
a wide range of diverse mechanisms during a genomic experiment campaign. We
provide theoretical guarantees of approximate optimality under standard
assumptions, and conduct a comprehensive experimental evaluation covering both
synthetic as well as real-world experimental design tasks. DiscoBAX outperforms
existing state-of-the-art methods for experimental design, selecting effective
and diverse perturbations in biological systems.
| [
{
"created": "Thu, 7 Dec 2023 06:05:39 GMT",
"version": "v1"
}
] | 2023-12-08 | [
[
"Lyle",
"Clare",
""
],
[
"Mehrjou",
"Arash",
""
],
[
"Notin",
"Pascal",
""
],
[
"Jesson",
"Andrew",
""
],
[
"Bauer",
"Stefan",
""
],
[
"Gal",
"Yarin",
""
],
[
"Schwab",
"Patrick",
""
]
] | The discovery of therapeutics to treat genetically-driven pathologies relies on identifying genes involved in the underlying disease mechanisms. Existing approaches search over the billions of potential interventions to maximize the expected influence on the target phenotype. However, to reduce the risk of failure in future stages of trials, practical experiment design aims to find a set of interventions that maximally change a target phenotype via diverse mechanisms. We propose DiscoBAX, a sample-efficient method for maximizing the rate of significant discoveries per experiment while simultaneously probing for a wide range of diverse mechanisms during a genomic experiment campaign. We provide theoretical guarantees of approximate optimality under standard assumptions, and conduct a comprehensive experimental evaluation covering both synthetic as well as real-world experimental design tasks. DiscoBAX outperforms existing state-of-the-art methods for experimental design, selecting effective and diverse perturbations in biological systems. |
2310.15202 | Nimisha Ghosh | Nimisha Ghosh and Daniele Santoni and Indrajit Saha and Giovanni
Felici | Predicting Transcription Factor Binding Sites using Transformer based
Capsule Network | null | null | null | null | q-bio.GN cs.AI cs.LG | http://creativecommons.org/licenses/by/4.0/ | Prediction of binding sites for transcription factors is important to
understand how they regulate gene expression and how this regulation can be
modulated for therapeutic purposes. Although in the past few years there are
significant works addressing this issue, there is still space for improvement.
In this regard, a transformer based capsule network viz. DNABERT-Cap is
proposed in this work to predict transcription factor binding sites mining
ChIP-seq datasets. DNABERT-Cap is a bidirectional encoder pre-trained with
large number of genomic DNA sequences, empowered with a capsule layer
responsible for the final prediction. The proposed model builds a predictor for
transcription factor binding sites using the joint optimisation of features
encompassing both bidirectional encoder and capsule layer, along with
convolutional and bidirectional long-short term memory layers. To evaluate the
efficiency of the proposed approach, we use a benchmark ChIP-seq datasets of
five cell lines viz. A549, GM12878, Hep-G2, H1-hESC and Hela, available in the
ENCODE repository. The results show that the average area under the receiver
operating characteristic curve score exceeds 0.91 for all such five cell lines.
DNABERT-Cap is also compared with existing state-of-the-art deep learning based
predictors viz. DeepARC, DeepTF, CNN-Zeng and DeepBind, and is seen to
outperform them.
| [
{
"created": "Mon, 23 Oct 2023 09:08:57 GMT",
"version": "v1"
},
{
"created": "Thu, 28 Dec 2023 18:25:20 GMT",
"version": "v2"
}
] | 2023-12-29 | [
[
"Ghosh",
"Nimisha",
""
],
[
"Santoni",
"Daniele",
""
],
[
"Saha",
"Indrajit",
""
],
[
"Felici",
"Giovanni",
""
]
] | Prediction of binding sites for transcription factors is important to understand how they regulate gene expression and how this regulation can be modulated for therapeutic purposes. Although in the past few years there are significant works addressing this issue, there is still space for improvement. In this regard, a transformer based capsule network viz. DNABERT-Cap is proposed in this work to predict transcription factor binding sites mining ChIP-seq datasets. DNABERT-Cap is a bidirectional encoder pre-trained with large number of genomic DNA sequences, empowered with a capsule layer responsible for the final prediction. The proposed model builds a predictor for transcription factor binding sites using the joint optimisation of features encompassing both bidirectional encoder and capsule layer, along with convolutional and bidirectional long-short term memory layers. To evaluate the efficiency of the proposed approach, we use a benchmark ChIP-seq datasets of five cell lines viz. A549, GM12878, Hep-G2, H1-hESC and Hela, available in the ENCODE repository. The results show that the average area under the receiver operating characteristic curve score exceeds 0.91 for all such five cell lines. DNABERT-Cap is also compared with existing state-of-the-art deep learning based predictors viz. DeepARC, DeepTF, CNN-Zeng and DeepBind, and is seen to outperform them. |
2407.13118 | Lingbin Bian | Lingbin Bian, Nizhuan Wang, Yuanning Li, Adeel Razi, Qian Wang, Han
Zhang, Dinggang Shen, and the UNC/UMN Baby Connectome Project Consortium | Evaluating the evolution and inter-individual variability of infant
functional module development from 0 to 5 years old | null | null | null | null | q-bio.NC stat.CO | http://creativecommons.org/licenses/by/4.0/ | The segregation and integration of infant brain networks undergo tremendous
changes due to the rapid development of brain function and organization.
Traditional methods for estimating brain modularity usually rely on
group-averaged functional connectivity (FC), often overlooking individual
variability. To address this, we introduce a novel approach utilizing Bayesian
modeling to analyze the dynamic development of functional modules in infants
over time. This method retains inter-individual variability and, in comparison
to conventional group averaging techniques, more effectively detects modules,
taking into account the stationarity of module evolution. Furthermore, we
explore gender differences in module development under awake and sleep
conditions by assessing modular similarities. Our results show that female
infants demonstrate more distinct modular structures between these two
conditions, possibly implying relative quiet and restful sleep compared with
male infants.
| [
{
"created": "Thu, 18 Jul 2024 02:57:46 GMT",
"version": "v1"
}
] | 2024-07-19 | [
[
"Bian",
"Lingbin",
""
],
[
"Wang",
"Nizhuan",
""
],
[
"Li",
"Yuanning",
""
],
[
"Razi",
"Adeel",
""
],
[
"Wang",
"Qian",
""
],
[
"Zhang",
"Han",
""
],
[
"Shen",
"Dinggang",
""
],
[
"Consortium",
"the UNC/UMN Baby Connectome Project",
""
]
] | The segregation and integration of infant brain networks undergo tremendous changes due to the rapid development of brain function and organization. Traditional methods for estimating brain modularity usually rely on group-averaged functional connectivity (FC), often overlooking individual variability. To address this, we introduce a novel approach utilizing Bayesian modeling to analyze the dynamic development of functional modules in infants over time. This method retains inter-individual variability and, in comparison to conventional group averaging techniques, more effectively detects modules, taking into account the stationarity of module evolution. Furthermore, we explore gender differences in module development under awake and sleep conditions by assessing modular similarities. Our results show that female infants demonstrate more distinct modular structures between these two conditions, possibly implying relative quiet and restful sleep compared with male infants. |
2306.02100 | Marc H\"utt | Isabella-Hilda Mendler and Barbara Drossel and Marc-Thorsten H\"utt | Microbiome abundance patterns as attractors and the implications for the
inference of microbial interaction networks | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Inferring microbial interaction networks from abundance patterns is an
important approach to advance our understanding of microbial communities in
general and the human microbiome in particular. Here we suggest discriminating
two levels of information contained in microbial abundance data: (1) the
quantitative abundance values and (2) the pattern of presences and absences of
microbial organisms. The latter allows for a binary view on microbiome data and
a novel interpretation of microbial data as attractors, or more precisely as
fixed points, of a Boolean network.
Starting from these attractors, our aim is to infer an interaction network
between the species present in the microbiome samples. To accomplish this task,
we introduce a novel inference method that combines the previously published
ESABO (Entropy Shifts of Abundance vectors under Boolean Operations) method
with an evolutionary algorithm. The key idea of our approach is that the
inferred network should reproduce the original set of (observed) binary
abundance patterns as attractors.
We study the accuracy and runtime properties of this evolutionary method, as
well as its behavior under incomplete knowledge of the attractor sets. Based on
this theoretical understanding of the method we then show an application to
empirical data.
| [
{
"created": "Sat, 3 Jun 2023 12:42:40 GMT",
"version": "v1"
}
] | 2023-06-06 | [
[
"Mendler",
"Isabella-Hilda",
""
],
[
"Drossel",
"Barbara",
""
],
[
"Hütt",
"Marc-Thorsten",
""
]
] | Inferring microbial interaction networks from abundance patterns is an important approach to advance our understanding of microbial communities in general and the human microbiome in particular. Here we suggest discriminating two levels of information contained in microbial abundance data: (1) the quantitative abundance values and (2) the pattern of presences and absences of microbial organisms. The latter allows for a binary view on microbiome data and a novel interpretation of microbial data as attractors, or more precisely as fixed points, of a Boolean network. Starting from these attractors, our aim is to infer an interaction network between the species present in the microbiome samples. To accomplish this task, we introduce a novel inference method that combines the previously published ESABO (Entropy Shifts of Abundance vectors under Boolean Operations) method with an evolutionary algorithm. The key idea of our approach is that the inferred network should reproduce the original set of (observed) binary abundance patterns as attractors. We study the accuracy and runtime properties of this evolutionary method, as well as its behavior under incomplete knowledge of the attractor sets. Based on this theoretical understanding of the method we then show an application to empirical data. |
1308.3721 | Roeland M.H. Merks | Ren\'e F.M. van Oers, Elisabeth G. Rens, Danielle J. LaValley, Cynthia
Reinhart-King, and Roeland M.H. Merks | Mechanical cell-matrix feedback explains pairwise and collective
endothelial cell behavior in vitro | 25 pages, 6 figures, accepted for publication in PLoS Computational
Biology | PLoS Comput Biol 10(8): e1003774, 2014 | 10.1371/journal.pcbi.1003774 | null | q-bio.CB nlin.CG nlin.PS q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In vitro cultures of endothelial cells are a widely used model system of the
collective behavior of endothelial cells during vasculogenesis and
angiogenesis. When seeded in an extracellular matrix, endothelial cells can
form blood vessel-like structures, including vascular networks and sprouts.
Endothelial morphogenesis depends on a large number of chemical and mechanical
factors, including the compliancy of the extracellular matrix, the available
growth factors, the adhesion of cells to the extracellular matrix, cell-cell
signaling, etc. Although various computational models have been proposed to
explain the role of each of these biochemical and biomechanical effects, the
understanding of the mechanisms underlying in vitro angiogenesis is still
incomplete. Most explanations focus on predicting the whole vascular network or
sprout from the underlying cell behavior, and do not check if the same model
also correctly captures the intermediate scale: the pairwise cell-cell
interactions or single cell responses to ECM mechanics. Here we show, using a
hybrid cellular Potts and finite element computational model, that a single set
of biologically plausible rules describing (a) the contractile forces that
endothelial cells exert on the ECM, (b) the resulting strains in the
extracellular matrix, and (c) the cellular response to the strains, suffices
for reproducing the behavior of individual endothelial cells and the
interactions of endothelial cell pairs in compliant matrices. With the same set
of rules, the model also reproduces network formation from scattered cells, and
sprouting from endothelial spheroids. Combining the present mechanical model
with aspects of previously proposed mechanical and chemical models may lead to
a more complete understanding of in vitro angiogenesis.
| [
{
"created": "Fri, 16 Aug 2013 21:02:03 GMT",
"version": "v1"
},
{
"created": "Fri, 4 Jul 2014 10:33:27 GMT",
"version": "v2"
}
] | 2014-08-15 | [
[
"van Oers",
"René F. M.",
""
],
[
"Rens",
"Elisabeth G.",
""
],
[
"LaValley",
"Danielle J.",
""
],
[
"Reinhart-King",
"Cynthia",
""
],
[
"Merks",
"Roeland M. H.",
""
]
] | In vitro cultures of endothelial cells are a widely used model system of the collective behavior of endothelial cells during vasculogenesis and angiogenesis. When seeded in an extracellular matrix, endothelial cells can form blood vessel-like structures, including vascular networks and sprouts. Endothelial morphogenesis depends on a large number of chemical and mechanical factors, including the compliancy of the extracellular matrix, the available growth factors, the adhesion of cells to the extracellular matrix, cell-cell signaling, etc. Although various computational models have been proposed to explain the role of each of these biochemical and biomechanical effects, the understanding of the mechanisms underlying in vitro angiogenesis is still incomplete. Most explanations focus on predicting the whole vascular network or sprout from the underlying cell behavior, and do not check if the same model also correctly captures the intermediate scale: the pairwise cell-cell interactions or single cell responses to ECM mechanics. Here we show, using a hybrid cellular Potts and finite element computational model, that a single set of biologically plausible rules describing (a) the contractile forces that endothelial cells exert on the ECM, (b) the resulting strains in the extracellular matrix, and (c) the cellular response to the strains, suffices for reproducing the behavior of individual endothelial cells and the interactions of endothelial cell pairs in compliant matrices. With the same set of rules, the model also reproduces network formation from scattered cells, and sprouting from endothelial spheroids. Combining the present mechanical model with aspects of previously proposed mechanical and chemical models may lead to a more complete understanding of in vitro angiogenesis. |
2009.10615 | Danko Georgiev | Danko D. Georgiev, Stefan K. Kolev, Eliahu Cohen, James F. Glazebrook | Computational capacity of pyramidal neurons in the cerebral cortex | 18 pages, 4 figures | Brain Research 2020; 1748: 147069 | 10.1016/j.brainres.2020.147069 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The electric activities of cortical pyramidal neurons are supported by
structurally stable, morphologically complex axo-dendritic trees. Anatomical
differences between axons and dendrites in regard to their length or caliber
reflect the underlying functional specializations, for input or output of
neural information, respectively. For a proper assessment of the computational
capacity of pyramidal neurons, we have analyzed an extensive dataset of
three-dimensional digital reconstructions from the NeuroMorpho.Org database,
and quantified basic dendritic or axonal morphometric measures in different
regions and layers of the mouse, rat or human cerebral cortex. Physical
estimates of the total number and type of ions involved in neuronal electric
spiking based on the obtained morphometric data, combined with energetics of
neurotransmitter release and signaling fueled by glucose consumed by the active
brain, support highly efficient cerebral computation performed at the
thermodynamically allowed Landauer limit for implementation of irreversible
logical operations. Individual proton tunneling events in voltage-sensing S4
protein $\alpha$-helices of Na$^{+}$, K$^{+}$ or Ca$^{2+}$ ion channels are
ideally suited to serve as single Landauer elementary logical operations that
are then amplified by selective ionic currents traversing the open channel
pores. This miniaturization of computational gating allows the execution of
over 1.2 zetta logical operations per second in the human cerebral cortex
without combusting the brain by the released heat.
| [
{
"created": "Thu, 3 Sep 2020 05:42:29 GMT",
"version": "v1"
}
] | 2020-09-23 | [
[
"Georgiev",
"Danko D.",
""
],
[
"Kolev",
"Stefan K.",
""
],
[
"Cohen",
"Eliahu",
""
],
[
"Glazebrook",
"James F.",
""
]
] | The electric activities of cortical pyramidal neurons are supported by structurally stable, morphologically complex axo-dendritic trees. Anatomical differences between axons and dendrites in regard to their length or caliber reflect the underlying functional specializations, for input or output of neural information, respectively. For a proper assessment of the computational capacity of pyramidal neurons, we have analyzed an extensive dataset of three-dimensional digital reconstructions from the NeuroMorpho.Org database, and quantified basic dendritic or axonal morphometric measures in different regions and layers of the mouse, rat or human cerebral cortex. Physical estimates of the total number and type of ions involved in neuronal electric spiking based on the obtained morphometric data, combined with energetics of neurotransmitter release and signaling fueled by glucose consumed by the active brain, support highly efficient cerebral computation performed at the thermodynamically allowed Landauer limit for implementation of irreversible logical operations. Individual proton tunneling events in voltage-sensing S4 protein $\alpha$-helices of Na$^{+}$, K$^{+}$ or Ca$^{2+}$ ion channels are ideally suited to serve as single Landauer elementary logical operations that are then amplified by selective ionic currents traversing the open channel pores. This miniaturization of computational gating allows the execution of over 1.2 zetta logical operations per second in the human cerebral cortex without combusting the brain by the released heat. |
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