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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
q-bio/0611016
|
John Bechhoefer
|
John Bechhoefer and Brandon Marshall
|
How Xenopus laevis replicates DNA reliably even though its origins of
replication are located and initiated stochastically
|
10 pages, 4 figures
|
Phys. Rev. Lett. 98, 098105 (2007)
|
10.1103/PhysRevLett.98.098105
| null |
q-bio.CB q-bio.QM
| null |
DNA replication in Xenopus laevis is extremely reliable, failing to complete
before cell division no more than once in 10,000 times; yet replication origins
sites are located and initiated stochastically. Using a model based on 1d
theories of nucleation and growth and using concepts from extreme-value
statistics, we derive the distribution of replication times given a particular
initiation function. We show that the experimentally observed initiation
strategy for Xenopus laevis meets the reliability constraint and is close to
the one that requires the fewest resources of a cell.
|
[
{
"created": "Sat, 4 Nov 2006 23:40:07 GMT",
"version": "v1"
}
] |
2015-04-02
|
[
[
"Bechhoefer",
"John",
""
],
[
"Marshall",
"Brandon",
""
]
] |
DNA replication in Xenopus laevis is extremely reliable, failing to complete before cell division no more than once in 10,000 times; yet replication origins sites are located and initiated stochastically. Using a model based on 1d theories of nucleation and growth and using concepts from extreme-value statistics, we derive the distribution of replication times given a particular initiation function. We show that the experimentally observed initiation strategy for Xenopus laevis meets the reliability constraint and is close to the one that requires the fewest resources of a cell.
|
2404.14658
|
Guerard Byrne
|
Guerard Byrne and Christopher McGregor
|
Anti-pig Antibodies in Swine Veterinarian Serum: Implications for
Clinical Xenotransplantation
|
13 pages, 2 Tables, 3 Figures
| null | null | null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Recent clinical xenotransplantation and human decedent studies demonstrate
that clinical hyperacute rejection of genetically engineered porcine organs can
be reliably avoided but that antibody mediated rejection continues to limit
graft survival. We previously identified porcine glycans and proteins which are
immunogenic after cardiac xenotransplantation in nonhuman primates, but the
clinical immune response to antigens present in glycan depleted triple knockout
(TKO) donor pigs is poorly understood. In this study we use fluorescence
barcoded HEK cells and HEK cell lines expressing porcine glycans (Gal and SDa)
or proteins (CD9, CD46, CD59, PROCR and ANXA2) to screen antibody reactivity in
human serum from 160 swine veterinarians, a serum source with potential
occupational immune challenge from porcine tissues and pathogens. High levels
of anti-Gal IgM were present in all samples and lower levels of anti-SDa IgM
were present in 41% of samples. IgM binding to porcine proteins, primarily CD9
and CD46, previously identified as immunogenic in pig to non-human primate
cardiac xenograft recipients, was detected in 28 of the 160 swine veterinarian
samples. These results suggest that barcoded HEK cell lines expressing porcine
protein antigens can be useful for screening human patient serum. A
comprehensive analysis of sera from clinical xenotransplant recipients to
define a panel of commonly immunogenic porcine antigens will likely be
necessary to establish an array of porcine non-Gal antigens for effective
monitoring of patient immune responses and allow earlier therapies to reverse
antibody mediated rejection.
|
[
{
"created": "Tue, 23 Apr 2024 01:41:48 GMT",
"version": "v1"
}
] |
2024-04-24
|
[
[
"Byrne",
"Guerard",
""
],
[
"McGregor",
"Christopher",
""
]
] |
Recent clinical xenotransplantation and human decedent studies demonstrate that clinical hyperacute rejection of genetically engineered porcine organs can be reliably avoided but that antibody mediated rejection continues to limit graft survival. We previously identified porcine glycans and proteins which are immunogenic after cardiac xenotransplantation in nonhuman primates, but the clinical immune response to antigens present in glycan depleted triple knockout (TKO) donor pigs is poorly understood. In this study we use fluorescence barcoded HEK cells and HEK cell lines expressing porcine glycans (Gal and SDa) or proteins (CD9, CD46, CD59, PROCR and ANXA2) to screen antibody reactivity in human serum from 160 swine veterinarians, a serum source with potential occupational immune challenge from porcine tissues and pathogens. High levels of anti-Gal IgM were present in all samples and lower levels of anti-SDa IgM were present in 41% of samples. IgM binding to porcine proteins, primarily CD9 and CD46, previously identified as immunogenic in pig to non-human primate cardiac xenograft recipients, was detected in 28 of the 160 swine veterinarian samples. These results suggest that barcoded HEK cell lines expressing porcine protein antigens can be useful for screening human patient serum. A comprehensive analysis of sera from clinical xenotransplant recipients to define a panel of commonly immunogenic porcine antigens will likely be necessary to establish an array of porcine non-Gal antigens for effective monitoring of patient immune responses and allow earlier therapies to reverse antibody mediated rejection.
|
1206.0529
|
Mustafa Barasa
|
M. Barasa, Z.W. Ng'ang'a, G.A. Sowayi, J.M. Okoth, M.B.O. Barasa,
F.B.M. Namulanda, E.A. Kagasi, M.M. Gicheru and S.H. Ozwara
|
Cytokine expression in malaria-infected non-human primate placentas
|
Open Veterinary Journal 1st June 2012. Seven pages, Three Figures.
arXiv admin note: text overlap with arXiv:1201.3232
|
M. Barasa, Z.W. Ng'ang'a et al. Cytokine expression in
malaria-infected non-human primate placentas. Open Veterinary Journal,
(2012), Vol. 2: 58-64
| null | null |
q-bio.CB q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Malaria parasites are known to mediate the induction of inflammatory immune
responses at the maternal-foetal interface during placental malaria (PM)
leading to adverse consequences like pre-term deliveries and abortions.
Immunological events that take place within the malaria-infected placental
micro-environment leading to retarded foetal growth and disruption of
pregnancies are among the critical parameters that are still in need of further
elucidation. The establishment of more animal models for studying placental
malaria can provide novel ways of circumventing problems experienced during
placental malaria research in humans such as inaccurate estimation of
gestational ages. Using the newly established olive baboon (Papio
anubis)-Plasmodium knowlesi (P. knowlesi) H strain model of placental malaria,
experiments were carried out to determine placental cytokine profiles
underlying the immunopathogenesis of placental malaria. Four pregnant olive
baboons were infected with blood stage P. knowlesi H strain parasites on the
one fiftieth day of gestation while four other uninfected pregnant olive
baboons were maintained as uninfected controls. After nine days of infection,
placentas were extracted from all the eight baboons through cesarean surgery
and used for the processing of placental plasma and sera samples for cytokine
sandwich enzyme linked immunosorbent assays (ELISA). Results indicated that the
occurrence of placental malaria was associated with elevated concentrations of
tumour necrosis factor alpha (TNF-{\alpha}) and interleukin 12 (IL-12).
Increased levels of IL-4, IL-6 and IL-10 and interferon gamma (IFN-{\gamma})
levels were detected in uninfected placentas. These findings match previous
reports regarding immunity during PM thereby demonstrating the reliability of
the olive baboon-P. knowlesi model for use in further studies.
|
[
{
"created": "Mon, 4 Jun 2012 06:44:57 GMT",
"version": "v1"
}
] |
2012-06-05
|
[
[
"Barasa",
"M.",
""
],
[
"Ng'ang'a",
"Z. W.",
""
],
[
"Sowayi",
"G. A.",
""
],
[
"Okoth",
"J. M.",
""
],
[
"Barasa",
"M. B. O.",
""
],
[
"Namulanda",
"F. B. M.",
""
],
[
"Kagasi",
"E. A.",
""
],
[
"Gicheru",
"M. M.",
""
],
[
"Ozwara",
"S. H.",
""
]
] |
Malaria parasites are known to mediate the induction of inflammatory immune responses at the maternal-foetal interface during placental malaria (PM) leading to adverse consequences like pre-term deliveries and abortions. Immunological events that take place within the malaria-infected placental micro-environment leading to retarded foetal growth and disruption of pregnancies are among the critical parameters that are still in need of further elucidation. The establishment of more animal models for studying placental malaria can provide novel ways of circumventing problems experienced during placental malaria research in humans such as inaccurate estimation of gestational ages. Using the newly established olive baboon (Papio anubis)-Plasmodium knowlesi (P. knowlesi) H strain model of placental malaria, experiments were carried out to determine placental cytokine profiles underlying the immunopathogenesis of placental malaria. Four pregnant olive baboons were infected with blood stage P. knowlesi H strain parasites on the one fiftieth day of gestation while four other uninfected pregnant olive baboons were maintained as uninfected controls. After nine days of infection, placentas were extracted from all the eight baboons through cesarean surgery and used for the processing of placental plasma and sera samples for cytokine sandwich enzyme linked immunosorbent assays (ELISA). Results indicated that the occurrence of placental malaria was associated with elevated concentrations of tumour necrosis factor alpha (TNF-{\alpha}) and interleukin 12 (IL-12). Increased levels of IL-4, IL-6 and IL-10 and interferon gamma (IFN-{\gamma}) levels were detected in uninfected placentas. These findings match previous reports regarding immunity during PM thereby demonstrating the reliability of the olive baboon-P. knowlesi model for use in further studies.
|
1303.4784
|
Matthew Wyczalkowski
|
Matthew A. Wyczalkowski and Victor D. Varner and Larry A. Taber
|
Computational and Experimental Study of the Mechanics of Embryonic Wound
Healing
|
32 pages, 13 figures
| null |
10.1016/j.bpj.2012.11.1764
| null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Wounds in the embryo show a remarkable ability to heal quickly without
leaving a scar. Previous studies have found that an actomyosin ring ("purse
string") forms around the wound perimeter and contracts to close the wound over
the course of several dozens of minutes. Here, we report experiments that
reveal an even faster mechanism which remarkably closes wounds by more than 50%
within the first 30 seconds. Circular and elliptical wounds (~100 um in size)
were made in the blastoderm of early chick embryos and allowed to heal, with
wound area and shape characterized as functions of time. The closure rate
displayed a biphasic behavior, with rapid constriction lasting about a minute,
followed by a period of more gradual closure to complete healing. Fluorescent
staining suggests that both healing phases are driven by actomyosin
contraction, with relatively rapid contraction of fibers at cell borders within
a relatively thick ring of tissue (several cells wide) around the wound
followed by slower contraction of a thin supracellular actomyosin ring along
the margin, consistent with a purse string mechanism. Finite-element modeling
showed that this idea is biophysically plausible, with relatively isotropic
contraction within the thick ring giving way to tangential contraction in the
thin ring. In addition, consistent with experimental results, simulated
elliptical wounds heal with little change in aspect ratio, and decreased
membrane tension can cause these wounds to open briefly before going on to
heal. These results provide new insight into the healing mechanism in embryonic
epithelia.
|
[
{
"created": "Tue, 19 Mar 2013 22:55:05 GMT",
"version": "v1"
},
{
"created": "Wed, 4 Sep 2013 00:28:32 GMT",
"version": "v2"
},
{
"created": "Fri, 6 Sep 2013 03:38:16 GMT",
"version": "v3"
}
] |
2015-06-15
|
[
[
"Wyczalkowski",
"Matthew A.",
""
],
[
"Varner",
"Victor D.",
""
],
[
"Taber",
"Larry A.",
""
]
] |
Wounds in the embryo show a remarkable ability to heal quickly without leaving a scar. Previous studies have found that an actomyosin ring ("purse string") forms around the wound perimeter and contracts to close the wound over the course of several dozens of minutes. Here, we report experiments that reveal an even faster mechanism which remarkably closes wounds by more than 50% within the first 30 seconds. Circular and elliptical wounds (~100 um in size) were made in the blastoderm of early chick embryos and allowed to heal, with wound area and shape characterized as functions of time. The closure rate displayed a biphasic behavior, with rapid constriction lasting about a minute, followed by a period of more gradual closure to complete healing. Fluorescent staining suggests that both healing phases are driven by actomyosin contraction, with relatively rapid contraction of fibers at cell borders within a relatively thick ring of tissue (several cells wide) around the wound followed by slower contraction of a thin supracellular actomyosin ring along the margin, consistent with a purse string mechanism. Finite-element modeling showed that this idea is biophysically plausible, with relatively isotropic contraction within the thick ring giving way to tangential contraction in the thin ring. In addition, consistent with experimental results, simulated elliptical wounds heal with little change in aspect ratio, and decreased membrane tension can cause these wounds to open briefly before going on to heal. These results provide new insight into the healing mechanism in embryonic epithelia.
|
2104.11739
|
Carlo Fulvi Mari Ph.D.
|
Carlo Fulvi Mari
|
Memory retrieval dynamics and storage capacity of a modular network
model of association cortex with featural decomposition
|
v2: 17 pages, 7+2 figures, pdflatex. Minor Revision: Further
observations and references were included, the wording of some paragraphs was
improved, and several typos were corrected
|
BioSystems 211, 104570 (2022)
|
10.1016/j.biosystems.2021.104570
| null |
q-bio.NC cond-mat.dis-nn physics.bio-ph
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
The primate heteromodal cortex presents an evident functional modularity at a
mesoscopic level, with physiological and anatomical evidence pointing to it as
likely substrate of long-term memory. In order to investigate some of its
properties, a model of multimodular autoassociator is studied. Each of the many
modules represents a neocortical functional ensemble of recurrently connected
neurons and operates as a Hebbian autoassociator, storing a number of local
features which it can recall upon cue. The global memory patterns are made of
combinations of features sparsely distributed across the modules. Intermodular
connections are modelled as a finite-connectivity random graph. Any pair of
features in any respective pair of modules is allowed to be involved in several
memory patterns; the coarse-grained modular network dynamics is defined in such
a way as to overcome the consequent ambiguity of associations. Effects of
long-range homeostatic synaptic scaling on network performance are also
assessed.
The dynamical process of cued retrieval almost saturates a natural upper
bound while producing negligible spurious activation. The extent of finite-size
effects on storage capacity is quantitatively evaluated. In the limit of
infinite size, the functional relationship between storage capacity and number
of features per module reduces to that which other authors found by methods
from equilibrium statistical mechanics, which suggests that the origin of the
functional form is of a combinatorial nature. In contrast with its apparent
inevitability at intramodular level, long-range synaptic scaling results to be
of minor relevance to both retrieval and storage capacity, casting doubt on its
existence in the neocortex. A conjecture is also posited about how statistical
fluctuation of connectivity across the network may underpin spontaneous
emergence of semantic hierarchies through learning.
|
[
{
"created": "Fri, 23 Apr 2021 17:50:49 GMT",
"version": "v1"
},
{
"created": "Tue, 7 Dec 2021 21:43:19 GMT",
"version": "v2"
}
] |
2021-12-09
|
[
[
"Mari",
"Carlo Fulvi",
""
]
] |
The primate heteromodal cortex presents an evident functional modularity at a mesoscopic level, with physiological and anatomical evidence pointing to it as likely substrate of long-term memory. In order to investigate some of its properties, a model of multimodular autoassociator is studied. Each of the many modules represents a neocortical functional ensemble of recurrently connected neurons and operates as a Hebbian autoassociator, storing a number of local features which it can recall upon cue. The global memory patterns are made of combinations of features sparsely distributed across the modules. Intermodular connections are modelled as a finite-connectivity random graph. Any pair of features in any respective pair of modules is allowed to be involved in several memory patterns; the coarse-grained modular network dynamics is defined in such a way as to overcome the consequent ambiguity of associations. Effects of long-range homeostatic synaptic scaling on network performance are also assessed. The dynamical process of cued retrieval almost saturates a natural upper bound while producing negligible spurious activation. The extent of finite-size effects on storage capacity is quantitatively evaluated. In the limit of infinite size, the functional relationship between storage capacity and number of features per module reduces to that which other authors found by methods from equilibrium statistical mechanics, which suggests that the origin of the functional form is of a combinatorial nature. In contrast with its apparent inevitability at intramodular level, long-range synaptic scaling results to be of minor relevance to both retrieval and storage capacity, casting doubt on its existence in the neocortex. A conjecture is also posited about how statistical fluctuation of connectivity across the network may underpin spontaneous emergence of semantic hierarchies through learning.
|
1701.01433
|
Ignacio Arganda-Carreras
|
Ignacio Arganda-Carreras, Darcy G Gordon, Sara Arganda, Maxime
Beaudoin, James FA Traniello
|
Group-wise 3D registration based templates to study the evolution of ant
worker neuroanatomy
|
10 pages, 5 figures, preprint for conference (not reviewed)
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The evolutionary success of ants and other social insects is considered to be
intrinsically linked to division of labor and emergent collective intelligence.
The role of the brains of individual ants in generating these processes,
however, is poorly understood. One genus of ant of special interest is
Pheidole, which includes more than a thousand species, most of which are
dimorphic, i.e. their colonies contain two subcastes of workers: minors and
majors. Using confocal imaging and manual annotations, it has been demonstrated
that minor and major workers of different ages of three species of Pheidole
have distinct patterns of brain size and subregion scaling. However, these
studies require laborious effort to quantify brain region volumes and are
subject to potential bias. To address these issues, we propose a group-wise 3D
registration approach to build for the first time bias-free brain atlases of
intra- and inter-subcaste individuals and automatize the segmentation of new
individuals.
|
[
{
"created": "Thu, 5 Jan 2017 14:44:41 GMT",
"version": "v1"
},
{
"created": "Fri, 13 Jan 2017 17:14:08 GMT",
"version": "v2"
},
{
"created": "Wed, 8 Feb 2017 15:22:39 GMT",
"version": "v3"
},
{
"created": "Mon, 21 Aug 2017 20:13:06 GMT",
"version": "v4"
}
] |
2017-08-23
|
[
[
"Arganda-Carreras",
"Ignacio",
""
],
[
"Gordon",
"Darcy G",
""
],
[
"Arganda",
"Sara",
""
],
[
"Beaudoin",
"Maxime",
""
],
[
"Traniello",
"James FA",
""
]
] |
The evolutionary success of ants and other social insects is considered to be intrinsically linked to division of labor and emergent collective intelligence. The role of the brains of individual ants in generating these processes, however, is poorly understood. One genus of ant of special interest is Pheidole, which includes more than a thousand species, most of which are dimorphic, i.e. their colonies contain two subcastes of workers: minors and majors. Using confocal imaging and manual annotations, it has been demonstrated that minor and major workers of different ages of three species of Pheidole have distinct patterns of brain size and subregion scaling. However, these studies require laborious effort to quantify brain region volumes and are subject to potential bias. To address these issues, we propose a group-wise 3D registration approach to build for the first time bias-free brain atlases of intra- and inter-subcaste individuals and automatize the segmentation of new individuals.
|
2109.10449
|
Cody Petrie
|
Cody Petrie, Christian Anderson, Casie Maekawa, Travis Maekawa, Mark
K. Transtrum
|
The supremum principle selects simple, transferable models
|
6 pages, 3 figures
| null | null | null |
q-bio.QM cond-mat.stat-mech physics.bio-ph physics.data-an
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We consider how mathematical models enable predictions for conditions that
are qualitatively different from the training data. We propose techniques based
on information topology to find models that can apply their learning in regimes
for which there is no data. The first step is to use the Manifold Boundary
Approximation Method to construct simple, reduced models of target phenomena in
a data-driven way. We consider the set of all such reduced models and use the
topological relationships among them to reason about model selection for new,
unobserved phenomena. Given minimal models for several target behaviors, we
introduce the supremum principle as a criterion for selecting a new,
transferable model. The supremal model, i.e., the least upper bound, is the
simplest model that reduces to each of the target behaviors. We illustrate how
to discover supremal models with several examples; in each case, the supremal
model unifies causal mechanisms to transfer successfully to new target domains.
We use these examples to motivate a general algorithm that has formal
connections to theories of analogical reasoning in cognitive psychology.
|
[
{
"created": "Tue, 21 Sep 2021 22:28:16 GMT",
"version": "v1"
},
{
"created": "Fri, 11 Feb 2022 20:14:12 GMT",
"version": "v2"
},
{
"created": "Wed, 25 May 2022 21:36:39 GMT",
"version": "v3"
}
] |
2022-05-27
|
[
[
"Petrie",
"Cody",
""
],
[
"Anderson",
"Christian",
""
],
[
"Maekawa",
"Casie",
""
],
[
"Maekawa",
"Travis",
""
],
[
"Transtrum",
"Mark K.",
""
]
] |
We consider how mathematical models enable predictions for conditions that are qualitatively different from the training data. We propose techniques based on information topology to find models that can apply their learning in regimes for which there is no data. The first step is to use the Manifold Boundary Approximation Method to construct simple, reduced models of target phenomena in a data-driven way. We consider the set of all such reduced models and use the topological relationships among them to reason about model selection for new, unobserved phenomena. Given minimal models for several target behaviors, we introduce the supremum principle as a criterion for selecting a new, transferable model. The supremal model, i.e., the least upper bound, is the simplest model that reduces to each of the target behaviors. We illustrate how to discover supremal models with several examples; in each case, the supremal model unifies causal mechanisms to transfer successfully to new target domains. We use these examples to motivate a general algorithm that has formal connections to theories of analogical reasoning in cognitive psychology.
|
0801.4164
|
Matthias Kaschube
|
Matthias Kaschube, Michael Schnabel, Siegrid L\"owel and Fred Wolf
|
Inter-areal coordination of columnar architectures during visual
cortical development
|
30 pages, 1 table, 6 figures
| null |
10.1073/pnas.0901615106
| null |
q-bio.NC q-bio.QM
| null |
The occurrence of a critical period of plasticity in the visual cortex has
long been established, yet its function in normal development is not fully
understood. Here we show that as the late phase of the critical period unfolds,
different areas of cat visual cortex develop in a coordinated manner.
Orientation columns in areas V1 and V2 become matched in size in regions that
are mutually connected. The same age trend is found for such regions in the
left and right brain hemisphere. Our results indicate that a function of
critical period plasticity is to progressively coordinate the functional
architectures of different cortical areas - even across hemispheres.
|
[
{
"created": "Sun, 27 Jan 2008 22:48:53 GMT",
"version": "v1"
}
] |
2015-05-13
|
[
[
"Kaschube",
"Matthias",
""
],
[
"Schnabel",
"Michael",
""
],
[
"Löwel",
"Siegrid",
""
],
[
"Wolf",
"Fred",
""
]
] |
The occurrence of a critical period of plasticity in the visual cortex has long been established, yet its function in normal development is not fully understood. Here we show that as the late phase of the critical period unfolds, different areas of cat visual cortex develop in a coordinated manner. Orientation columns in areas V1 and V2 become matched in size in regions that are mutually connected. The same age trend is found for such regions in the left and right brain hemisphere. Our results indicate that a function of critical period plasticity is to progressively coordinate the functional architectures of different cortical areas - even across hemispheres.
|
q-bio/0401013
|
Tatiana Verechtchaguina
|
T. Verechtchaguina, L. Schimansky-Geier, I.M. Sokolov
|
Spectra and waiting-time densities in firing resonant and nonresonant
neurons
|
7 pages, 8 figures
|
Phys. Rev. E 70, 031916 (2004)
|
10.1103/PhysRevE.70.031916
| null |
q-bio.NC
| null |
The response of a neural cell to an external stimulus can follow one of the
two patterns: Nonresonant neurons monotonously relax to the resting state after
excitation while resonant ones show subthreshold oscillations. We investigate
how do these subthreshold properties of neurons affect their suprathreshold
response. Vice versa we ask: Can we distinguish between both types of neuronal
dynamics using suprathreshold spike trains? The dynamics of neurons is given by
stochastic FitzHugh-Nagumo and Morris-Lecar models with either having a focus
or a node as the stable fixpoint. We determine numerically the spectral power
density as well as the interspike interval density in response to a random
(noise-like) signals. We show that the information about the type of dynamics
obtained from power spectra is of limited validity. In contrast, the interspike
interval density gives a very sensitive instrument for the diagnostics of
whether the dynamics has resonant or nonresonant properties. For the latter
value we formulate a fit formula and use it to reconstruct theoretically the
spectral power density, which coincides with the numerically obtained spectra.
We underline that the renewal theory is applicable to analysis of
suprathreshold responses even of resonant neurons.
|
[
{
"created": "Thu, 8 Jan 2004 22:59:11 GMT",
"version": "v1"
},
{
"created": "Thu, 30 Jun 2005 15:06:00 GMT",
"version": "v2"
}
] |
2009-11-10
|
[
[
"Verechtchaguina",
"T.",
""
],
[
"Schimansky-Geier",
"L.",
""
],
[
"Sokolov",
"I. M.",
""
]
] |
The response of a neural cell to an external stimulus can follow one of the two patterns: Nonresonant neurons monotonously relax to the resting state after excitation while resonant ones show subthreshold oscillations. We investigate how do these subthreshold properties of neurons affect their suprathreshold response. Vice versa we ask: Can we distinguish between both types of neuronal dynamics using suprathreshold spike trains? The dynamics of neurons is given by stochastic FitzHugh-Nagumo and Morris-Lecar models with either having a focus or a node as the stable fixpoint. We determine numerically the spectral power density as well as the interspike interval density in response to a random (noise-like) signals. We show that the information about the type of dynamics obtained from power spectra is of limited validity. In contrast, the interspike interval density gives a very sensitive instrument for the diagnostics of whether the dynamics has resonant or nonresonant properties. For the latter value we formulate a fit formula and use it to reconstruct theoretically the spectral power density, which coincides with the numerically obtained spectra. We underline that the renewal theory is applicable to analysis of suprathreshold responses even of resonant neurons.
|
1412.7958
|
Alexander K. Vidybida
|
Alexander K.Vidybida
|
Relation between firing statistics of spiking neuron with instantaneous
feedback and without feedback
|
5 pages letter. In this version, section about moments and variances
is added, text style and language improved
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We consider a wide class of spiking neuron models, defined by rather general
set of conditions typical for basic models like leaky integrate and fire, or
binding neuron model. A neuron is fed with a point renewal process. A relation
between the three probability density functions (pdf): (i) pdf of input
interspike intervals, (ii) pdf of output interspike intervals of a neuron with
instantaneous feedback and (iii) pdf for that same neuron without feedback is
derived. This allows to calculate any of the three pdfs provided the another
two are given. Similar relation between corresponding means and variances is
derived. The relations are checked exactly for the binding neuron model.
|
[
{
"created": "Fri, 26 Dec 2014 16:50:28 GMT",
"version": "v1"
},
{
"created": "Thu, 8 Jan 2015 12:57:09 GMT",
"version": "v2"
},
{
"created": "Thu, 12 Feb 2015 14:59:51 GMT",
"version": "v3"
}
] |
2015-02-13
|
[
[
"Vidybida",
"Alexander K.",
""
]
] |
We consider a wide class of spiking neuron models, defined by rather general set of conditions typical for basic models like leaky integrate and fire, or binding neuron model. A neuron is fed with a point renewal process. A relation between the three probability density functions (pdf): (i) pdf of input interspike intervals, (ii) pdf of output interspike intervals of a neuron with instantaneous feedback and (iii) pdf for that same neuron without feedback is derived. This allows to calculate any of the three pdfs provided the another two are given. Similar relation between corresponding means and variances is derived. The relations are checked exactly for the binding neuron model.
|
1704.01761
|
Hans Trukenbrod
|
Hans A. Trukenbrod, Simon Barthelm\'e, Felix A. Wichmann and Ralf
Engbert
|
Spatial statistics for gaze patterns in scene viewing: Effects of
repeated viewing
|
27 pages, 10 figures
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Scene viewing is used to study attentional selection in complex but still
controlled environments. One of the main observations on eye movements during
scene viewing is the inhomogeneous distribution of fixation locations: While
some parts of an image are fixated by almost all observers and are inspected
repeatedly by the same observer, other image parts remain unfixated by
observers even after long exploration intervals. Here, we apply spatial point
process methods to investigate the relationship between pairs of fixations.
More precisely, we use the pair correlation function (PCF), a powerful
statistical tool, to evaluate dependencies between fixation locations along
individual scanpaths. We demonstrate that aggregation of fixation locations
within four degrees is stronger than expected from chance. Furthermore, the PCF
reveals stronger aggregation of fixations when the same image is presented a
second time. We use simulations of a dynamical model to show that a narrower
spatial attentional span may explain differences in pair correlations between
the first and the second inspection of the same image.
|
[
{
"created": "Thu, 6 Apr 2017 09:46:01 GMT",
"version": "v1"
},
{
"created": "Tue, 13 Nov 2018 08:35:59 GMT",
"version": "v2"
}
] |
2018-11-14
|
[
[
"Trukenbrod",
"Hans A.",
""
],
[
"Barthelmé",
"Simon",
""
],
[
"Wichmann",
"Felix A.",
""
],
[
"Engbert",
"Ralf",
""
]
] |
Scene viewing is used to study attentional selection in complex but still controlled environments. One of the main observations on eye movements during scene viewing is the inhomogeneous distribution of fixation locations: While some parts of an image are fixated by almost all observers and are inspected repeatedly by the same observer, other image parts remain unfixated by observers even after long exploration intervals. Here, we apply spatial point process methods to investigate the relationship between pairs of fixations. More precisely, we use the pair correlation function (PCF), a powerful statistical tool, to evaluate dependencies between fixation locations along individual scanpaths. We demonstrate that aggregation of fixation locations within four degrees is stronger than expected from chance. Furthermore, the PCF reveals stronger aggregation of fixations when the same image is presented a second time. We use simulations of a dynamical model to show that a narrower spatial attentional span may explain differences in pair correlations between the first and the second inspection of the same image.
|
2304.06273
|
Masod Sadipour
|
Masod Sadipour, Mohammad Masoud Momeni, Majid Soltani
|
Effect of hydraulic conductivity and permeability on drug distribution,
an investigation based on a part of a real tissue
|
15 pages
| null | null | null |
q-bio.TO cs.NA math.NA
|
http://creativecommons.org/publicdomain/zero/1.0/
|
In this study, a computational simulation is employed to place two essential
parameters, the permeability of vessels and hydraulic conductivity, under
assessment. These parameters impact the movement of drug particles through
vessels, and normal and tumoral tissue to examine the concentration of
nanoparticles, interstitial pressure, and velocity. To provide a geometric
model detailing the capillary network under normal and tumoral tissue
conditions, the geometry is extracted via real image processing. Subsequently,
the real conditions were considered to solve the equations pertaining to drug
transport and intravascular and interstitial flows in the tissue. The results
showed that an increase in permeability and hydraulic conductivity leads to an
increase in drug concentration in the tumor. Finally, Methotrexate drug has the
most effect in the treatment of tumors. Overall, the computational model for
anti-cancer delivery provides a powerful tool for understanding and optimizing
drug delivery strategies for the treatment of cancer.
|
[
{
"created": "Thu, 13 Apr 2023 05:16:36 GMT",
"version": "v1"
}
] |
2023-04-14
|
[
[
"Sadipour",
"Masod",
""
],
[
"Momeni",
"Mohammad Masoud",
""
],
[
"Soltani",
"Majid",
""
]
] |
In this study, a computational simulation is employed to place two essential parameters, the permeability of vessels and hydraulic conductivity, under assessment. These parameters impact the movement of drug particles through vessels, and normal and tumoral tissue to examine the concentration of nanoparticles, interstitial pressure, and velocity. To provide a geometric model detailing the capillary network under normal and tumoral tissue conditions, the geometry is extracted via real image processing. Subsequently, the real conditions were considered to solve the equations pertaining to drug transport and intravascular and interstitial flows in the tissue. The results showed that an increase in permeability and hydraulic conductivity leads to an increase in drug concentration in the tumor. Finally, Methotrexate drug has the most effect in the treatment of tumors. Overall, the computational model for anti-cancer delivery provides a powerful tool for understanding and optimizing drug delivery strategies for the treatment of cancer.
|
1206.0311
|
Pamela Reinagel
|
Pamela Reinagel, Emily Mankin, and Adam Calhoun
|
Speed and accuracy in a visual motion discrimination task as performed
by rats
|
Content is identical to a poster presented at the 2009 Society for
Neuroscience meeting: Reinagel P, Mankin E, and Calhoun A (2009) Speed and
accuracy in a visual motion discrimination task as performed by rats. Program
No. 281.12. 2009 Neuroscience Meeting Planner. Chicago, IL: Society for
Neuroscience, 2009. Online
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We find that rats, like primates and humans, perform better on the random dot
motion task when they take more time to respond. We provide evidence that this
improvement is due to stimulus integration. Rats increase their response
latency modestly as a function of trial difficulty. Rats can modulate response
latency more strongly on a trial by trial basis, apparently on the basis of
reward-related parameters.
|
[
{
"created": "Fri, 1 Jun 2012 21:26:53 GMT",
"version": "v1"
}
] |
2012-06-05
|
[
[
"Reinagel",
"Pamela",
""
],
[
"Mankin",
"Emily",
""
],
[
"Calhoun",
"Adam",
""
]
] |
We find that rats, like primates and humans, perform better on the random dot motion task when they take more time to respond. We provide evidence that this improvement is due to stimulus integration. Rats increase their response latency modestly as a function of trial difficulty. Rats can modulate response latency more strongly on a trial by trial basis, apparently on the basis of reward-related parameters.
|
2201.06687
|
Evan Johnson
|
Evan C. Johnson, Oscar Godoy, and Alan Hastings
|
The storage effect is not about bet-hedging or population
stage-structure
|
20 pages, 8 figures
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
The storage effect is a well-known explanation for coexistence in temporally
varying environments. Like many complex ecological theories, the storage effect
is often used as an explanation for observed coexistence on the basis of
heuristic understanding, rather than careful application of a detailed model.
One interpretation states that species coexist by specializing on specific
environmental states, and therefore must have a robust life-stage (e.g.,
long-lived adults, a seed-bank) in order to "wait it out" for favorable
conditions. Here we show that this widely employed interpretation can be
misleading. Multiple models show that stage-structure, long lifespans, and
overlapping generations are neither necessary nor sufficient for the storage
effect. In models where a robust life-stage does engender a storage effect, it
does not do so by preventing stochastic extinction or by improving relative
bet-hedging. A robust life-stage is best understood as one of many ways to
fulfill an abstract condition for the storage effect: an interaction effect of
environment and competition on per capita growth rates. Using a dataset of
annual plants from a Mediterranean grassland in Spain, we show that such
interaction effects occur between water availability and the number of
germinant competitors, leading to storage in the absence of a persistent seed
bank. Empiricists hoping to uncover the storage effect should look for
interaction effects between environmental conditions and competition -- easily
identifiable with multiple regression -- at all stages of a species'
life-cycle.
|
[
{
"created": "Tue, 18 Jan 2022 01:16:36 GMT",
"version": "v1"
},
{
"created": "Thu, 12 Jan 2023 04:43:13 GMT",
"version": "v2"
}
] |
2023-01-13
|
[
[
"Johnson",
"Evan C.",
""
],
[
"Godoy",
"Oscar",
""
],
[
"Hastings",
"Alan",
""
]
] |
The storage effect is a well-known explanation for coexistence in temporally varying environments. Like many complex ecological theories, the storage effect is often used as an explanation for observed coexistence on the basis of heuristic understanding, rather than careful application of a detailed model. One interpretation states that species coexist by specializing on specific environmental states, and therefore must have a robust life-stage (e.g., long-lived adults, a seed-bank) in order to "wait it out" for favorable conditions. Here we show that this widely employed interpretation can be misleading. Multiple models show that stage-structure, long lifespans, and overlapping generations are neither necessary nor sufficient for the storage effect. In models where a robust life-stage does engender a storage effect, it does not do so by preventing stochastic extinction or by improving relative bet-hedging. A robust life-stage is best understood as one of many ways to fulfill an abstract condition for the storage effect: an interaction effect of environment and competition on per capita growth rates. Using a dataset of annual plants from a Mediterranean grassland in Spain, we show that such interaction effects occur between water availability and the number of germinant competitors, leading to storage in the absence of a persistent seed bank. Empiricists hoping to uncover the storage effect should look for interaction effects between environmental conditions and competition -- easily identifiable with multiple regression -- at all stages of a species' life-cycle.
|
0810.4580
|
Tijana Ivancevic
|
Tijana T. Ivancevic, Murk J. Bottema and Lakhmi C. Jain
|
A Mathematical Model of Chaotic Attractor in Tumor Growth and Decay
|
4 pages, 1 figure, latex
| null | null | null |
q-bio.CB q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We propose a strange-attractor model of tumor growth and metastasis. It is a
4-dimensional spatio-temporal cancer model with strong nonlinear couplings.
Even the same type of tumor is different in every patient both in size and
appearance, as well as in temporal behavior. This is clearly a characteristic
of dynamical systems sensitive to initial conditions. The new chaotic model of
tumor growth and decay is biologically motivated. It has been developed as a
live Mathematica demonstration, see Wolfram Demonstrator site:
http://demonstrations.wolfram.com/ChaoticAttractorInTumorGrowth/ Key words:
Reaction-diffusion tumor growth model, chaotic attractor, sensitive dependence
on initial tumor characteristics
|
[
{
"created": "Mon, 27 Oct 2008 12:50:13 GMT",
"version": "v1"
}
] |
2008-10-28
|
[
[
"Ivancevic",
"Tijana T.",
""
],
[
"Bottema",
"Murk J.",
""
],
[
"Jain",
"Lakhmi C.",
""
]
] |
We propose a strange-attractor model of tumor growth and metastasis. It is a 4-dimensional spatio-temporal cancer model with strong nonlinear couplings. Even the same type of tumor is different in every patient both in size and appearance, as well as in temporal behavior. This is clearly a characteristic of dynamical systems sensitive to initial conditions. The new chaotic model of tumor growth and decay is biologically motivated. It has been developed as a live Mathematica demonstration, see Wolfram Demonstrator site: http://demonstrations.wolfram.com/ChaoticAttractorInTumorGrowth/ Key words: Reaction-diffusion tumor growth model, chaotic attractor, sensitive dependence on initial tumor characteristics
|
1806.04037
|
Andriy Temko Dr
|
Mark O'Sullivan, Sergi Gomez, Alison O'Shea, Eduard Salgado, Kevin
Huillca, Sean Mathieson, Geraldine Boylan, Emanuel Popovici, Andriy Temko
|
Neonatal EEG Interpretation and Decision Support Framework for Mobile
Platforms
|
EMBC 2018
| null | null | null |
q-bio.NC cs.SE stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This paper proposes and implements an intuitive and pervasive solution for
neonatal EEG monitoring assisted by sonification and deep learning AI that
provides information about neonatal brain health to all neonatal healthcare
professionals, particularly those without EEG interpretation expertise. The
system aims to increase the demographic of clinicians capable of diagnosing
abnormalities in neonatal EEG. The proposed system uses a low-cost and
low-power EEG acquisition system. An Android app provides single-channel EEG
visualization, traffic-light indication of the presence of neonatal seizures
provided by a trained, deep convolutional neural network and an algorithm for
EEG sonification, designed to facilitate the perception of changes in EEG
morphology specific to neonatal seizures. The multifaceted EEG interpretation
framework is presented and the implemented mobile platform architecture is
analyzed with respect to its power consumption and accuracy.
|
[
{
"created": "Fri, 8 Jun 2018 09:35:02 GMT",
"version": "v1"
}
] |
2018-06-12
|
[
[
"O'Sullivan",
"Mark",
""
],
[
"Gomez",
"Sergi",
""
],
[
"O'Shea",
"Alison",
""
],
[
"Salgado",
"Eduard",
""
],
[
"Huillca",
"Kevin",
""
],
[
"Mathieson",
"Sean",
""
],
[
"Boylan",
"Geraldine",
""
],
[
"Popovici",
"Emanuel",
""
],
[
"Temko",
"Andriy",
""
]
] |
This paper proposes and implements an intuitive and pervasive solution for neonatal EEG monitoring assisted by sonification and deep learning AI that provides information about neonatal brain health to all neonatal healthcare professionals, particularly those without EEG interpretation expertise. The system aims to increase the demographic of clinicians capable of diagnosing abnormalities in neonatal EEG. The proposed system uses a low-cost and low-power EEG acquisition system. An Android app provides single-channel EEG visualization, traffic-light indication of the presence of neonatal seizures provided by a trained, deep convolutional neural network and an algorithm for EEG sonification, designed to facilitate the perception of changes in EEG morphology specific to neonatal seizures. The multifaceted EEG interpretation framework is presented and the implemented mobile platform architecture is analyzed with respect to its power consumption and accuracy.
|
2009.12422
|
Daniel Martins
|
Daniel P. Martins, Huong Q.-O'Reilly, Lee Coffey, Paul D. Cotter,
Sasitharan Balasubramaniam
|
Hydrogel-based Bio-nanomachine Transmitters for Bacterial Molecular
Communications
|
This work has been submitted to an ACM conference for possible
publication
| null |
10.1145/3416006.3431271
| null |
q-bio.CB physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Bacterial quorum sensing can be engineered with a view to the design of
biotechnological applications based on their intrinsic role as a means of
communication. We propose the creation of a positive feedback loop that will
promote the emission of a superfolded green fluorescence protein from a
bacterial population that will flow through hydrogel, which is used to
encapsulate the cells. These engineered cells are heretofore referred to as
bio-nanomachine transmitters and we show that for lower values of diffusion
coefficient, a higher molecular output signal power can be produced, which
supports the use of engineered bacteria contained within hydrogels for
molecular communications systems. In addition, our wet lab results show the
propagation of the molecular output signal, proving the feasibility of
engineering a positive feedback loop to create a bio-nanomachine transmitter
that can be used for biosensing applications.
|
[
{
"created": "Fri, 25 Sep 2020 20:13:05 GMT",
"version": "v1"
}
] |
2021-04-15
|
[
[
"Martins",
"Daniel P.",
""
],
[
"-O'Reilly",
"Huong Q.",
""
],
[
"Coffey",
"Lee",
""
],
[
"Cotter",
"Paul D.",
""
],
[
"Balasubramaniam",
"Sasitharan",
""
]
] |
Bacterial quorum sensing can be engineered with a view to the design of biotechnological applications based on their intrinsic role as a means of communication. We propose the creation of a positive feedback loop that will promote the emission of a superfolded green fluorescence protein from a bacterial population that will flow through hydrogel, which is used to encapsulate the cells. These engineered cells are heretofore referred to as bio-nanomachine transmitters and we show that for lower values of diffusion coefficient, a higher molecular output signal power can be produced, which supports the use of engineered bacteria contained within hydrogels for molecular communications systems. In addition, our wet lab results show the propagation of the molecular output signal, proving the feasibility of engineering a positive feedback loop to create a bio-nanomachine transmitter that can be used for biosensing applications.
|
2110.15200
|
Matthew Ragoza
|
Matthew Ragoza, Tomohide Masuda, David Ryan Koes
|
Generating 3D Molecules Conditional on Receptor Binding Sites with Deep
Generative Models
|
Main: 12 pages, 7 figures; Supplement: 6 pages, 14 figures
| null | null | null |
q-bio.QM cs.LG
|
http://creativecommons.org/licenses/by-sa/4.0/
|
The goal of structure-based drug discovery is to find small molecules that
bind to a given target protein. Deep learning has been used to generate
drug-like molecules with certain cheminformatic properties, but has not yet
been applied to generating 3D molecules predicted to bind to proteins by
sampling the conditional distribution of protein-ligand binding interactions.
In this work, we describe for the first time a deep learning system for
generating 3D molecular structures conditioned on a receptor binding site. We
approach the problem using a conditional variational autoencoder trained on an
atomic density grid representation of cross-docked protein-ligand structures.
We apply atom fitting and bond inference procedures to construct valid
molecular conformations from generated atomic densities. We evaluate the
properties of the generated molecules and demonstrate that they change
significantly when conditioned on mutated receptors. We also explore the latent
space learned by our generative model using sampling and interpolation
techniques. This work opens the door for end-to-end prediction of stable
bioactive molecules from protein structures with deep learning.
|
[
{
"created": "Thu, 28 Oct 2021 15:17:24 GMT",
"version": "v1"
},
{
"created": "Wed, 26 Jan 2022 16:26:17 GMT",
"version": "v2"
}
] |
2022-01-27
|
[
[
"Ragoza",
"Matthew",
""
],
[
"Masuda",
"Tomohide",
""
],
[
"Koes",
"David Ryan",
""
]
] |
The goal of structure-based drug discovery is to find small molecules that bind to a given target protein. Deep learning has been used to generate drug-like molecules with certain cheminformatic properties, but has not yet been applied to generating 3D molecules predicted to bind to proteins by sampling the conditional distribution of protein-ligand binding interactions. In this work, we describe for the first time a deep learning system for generating 3D molecular structures conditioned on a receptor binding site. We approach the problem using a conditional variational autoencoder trained on an atomic density grid representation of cross-docked protein-ligand structures. We apply atom fitting and bond inference procedures to construct valid molecular conformations from generated atomic densities. We evaluate the properties of the generated molecules and demonstrate that they change significantly when conditioned on mutated receptors. We also explore the latent space learned by our generative model using sampling and interpolation techniques. This work opens the door for end-to-end prediction of stable bioactive molecules from protein structures with deep learning.
|
0806.1063
|
Suani Pinho
|
E. A. Reis, L. B. L. Santos, S. T. R. Pinho
|
A cellular automata model for avascular solid tumor growth under the
effect of therapy
|
18 pages, 15 figures (jpeg)
| null |
10.1016/j.physa.2008.11.038
| null |
q-bio.TO nlin.CG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Tumor growth has long been a target of investigation within the context of
mathematical and computer modelling. The objective of this study is to propose
and analyze a two-dimensional probabilistic cellular automata model to describe
avascular solid tumor growth, taking into account both the competition between
cancer cells and normal cells for nutrients and/or space and a time-dependent
proliferation of cancer cells. Gompertzian growth, characteristic of some
tumors, is described and some of the features of the time-spatial pattern of
solid tumors, such as compact morphology with irregular borders, are captured.
The parameter space is studied in order to analyze the occurrence of necrosis
and the response to therapy. Our findings suggest that transitions exist
between necrotic and non-necrotic phases (no-therapy cases), and between the
states of cure and non-cure (therapy cases). To analyze cure, the control and
order parameters are, respectively, the highest probability of cancer cell
proliferation and the probability of the therapeutic effect on cancer cells.
With respect to patterns, it is possible to observe the inner necrotic core and
the effect of the therapy destroying the tumor from its outer borders inwards.
|
[
{
"created": "Thu, 5 Jun 2008 21:48:37 GMT",
"version": "v1"
}
] |
2009-11-13
|
[
[
"Reis",
"E. A.",
""
],
[
"Santos",
"L. B. L.",
""
],
[
"Pinho",
"S. T. R.",
""
]
] |
Tumor growth has long been a target of investigation within the context of mathematical and computer modelling. The objective of this study is to propose and analyze a two-dimensional probabilistic cellular automata model to describe avascular solid tumor growth, taking into account both the competition between cancer cells and normal cells for nutrients and/or space and a time-dependent proliferation of cancer cells. Gompertzian growth, characteristic of some tumors, is described and some of the features of the time-spatial pattern of solid tumors, such as compact morphology with irregular borders, are captured. The parameter space is studied in order to analyze the occurrence of necrosis and the response to therapy. Our findings suggest that transitions exist between necrotic and non-necrotic phases (no-therapy cases), and between the states of cure and non-cure (therapy cases). To analyze cure, the control and order parameters are, respectively, the highest probability of cancer cell proliferation and the probability of the therapeutic effect on cancer cells. With respect to patterns, it is possible to observe the inner necrotic core and the effect of the therapy destroying the tumor from its outer borders inwards.
|
2111.01282
|
Ross Kedl
|
Ross M. Kedl
|
An immunological autobiography: my year as a COVID-19 vaccine trial
participant
| null | null | null | null |
q-bio.OT
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
I present here longitudinal evaluation of T and B cell immunity to SARS-CoV2
and variants of concern (VOC) from a single subject (me) over an entire year
post vaccination. After enrolling in the Moderna phase III clinical trial, I
collected my own biological samples pre- and post-immunization in the event of
being a recipient of the experimental vaccine. The evidence strongly supports
the conclusion that I did not receive the placebo. The analysis is admittedly
limited to an n of 1, but the results fit well with data taken from published
works and represent one of the more comprehensive longitudinal evaluations of
vaccine-elicited immunity within a single individual yet to be undertaken.
Though the data amount to a well-documented anecdote, given its granularity, it
is not without its insights and may be of further use in directing future
longitudinal studies that have actual statistical significance.
|
[
{
"created": "Mon, 1 Nov 2021 22:19:40 GMT",
"version": "v1"
},
{
"created": "Wed, 5 Jan 2022 22:41:05 GMT",
"version": "v2"
}
] |
2022-01-07
|
[
[
"Kedl",
"Ross M.",
""
]
] |
I present here longitudinal evaluation of T and B cell immunity to SARS-CoV2 and variants of concern (VOC) from a single subject (me) over an entire year post vaccination. After enrolling in the Moderna phase III clinical trial, I collected my own biological samples pre- and post-immunization in the event of being a recipient of the experimental vaccine. The evidence strongly supports the conclusion that I did not receive the placebo. The analysis is admittedly limited to an n of 1, but the results fit well with data taken from published works and represent one of the more comprehensive longitudinal evaluations of vaccine-elicited immunity within a single individual yet to be undertaken. Though the data amount to a well-documented anecdote, given its granularity, it is not without its insights and may be of further use in directing future longitudinal studies that have actual statistical significance.
|
1405.3331
|
Marcus Kaiser
|
Ana M. Mihut, Graham Morgan, Marcus Kaiser
|
Graphic Processing Unit Simulation of Axon Growth and Guidance through
Cue Diffusion on Massively Parallel Processors
|
Dynamic Connectome Lab, Technical Report 2
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Neural development represents not only an exciting and complex field of
study, with ongoing progress, but it also became the epicentre of neuroscience
and developmental biology, as it strives to describe the underlying cellular
and molecular mechanisms by which the central nervous system emerges during the
various levels of embryonic development phases. The nervous system is a dynamic
entity, where the genetic information plays an important role in shaping the
intra- and extracellular environments, which in turn offer a reliable
foundation for the stem cell precursors to divide and form neurons. Throughout
the embryonic development stages, the neurons undergo different processes:
migration at an immature level from the initial place in the embryo to a
predefined final position, axonal differentiation and guidance of the motile
growth cone towards a postsynaptic target, synaptic formation between axons and
target, and lastly long-term synaptic changes which underlie learning and
memory. In order to gain a better understanding of how the nervous system
develops, mathematical and computational models have been created and expanded
in order to bridge the gap between system-level dynamics and lower level
cellular and molecular processes. This research paper aims to illustrate the
potential of theoretical mathematical and computational models for analysing
one important stage of neural development - axonal growth and guidance
mechanisms in the presence of diffusion cues, through a visual simulation which
is optimized via the graphic processing unit and parallel programming
techniques.
|
[
{
"created": "Tue, 13 May 2014 23:57:39 GMT",
"version": "v1"
}
] |
2014-05-15
|
[
[
"Mihut",
"Ana M.",
""
],
[
"Morgan",
"Graham",
""
],
[
"Kaiser",
"Marcus",
""
]
] |
Neural development represents not only an exciting and complex field of study, with ongoing progress, but it also became the epicentre of neuroscience and developmental biology, as it strives to describe the underlying cellular and molecular mechanisms by which the central nervous system emerges during the various levels of embryonic development phases. The nervous system is a dynamic entity, where the genetic information plays an important role in shaping the intra- and extracellular environments, which in turn offer a reliable foundation for the stem cell precursors to divide and form neurons. Throughout the embryonic development stages, the neurons undergo different processes: migration at an immature level from the initial place in the embryo to a predefined final position, axonal differentiation and guidance of the motile growth cone towards a postsynaptic target, synaptic formation between axons and target, and lastly long-term synaptic changes which underlie learning and memory. In order to gain a better understanding of how the nervous system develops, mathematical and computational models have been created and expanded in order to bridge the gap between system-level dynamics and lower level cellular and molecular processes. This research paper aims to illustrate the potential of theoretical mathematical and computational models for analysing one important stage of neural development - axonal growth and guidance mechanisms in the presence of diffusion cues, through a visual simulation which is optimized via the graphic processing unit and parallel programming techniques.
|
1506.07889
|
Antonio Galves
|
D. Fraiman, M.F. Miranda, F. Erthal, P.F. Buur, M. Elschot, L. Souza,
S.A.R.B. Rombouts, M.J.P. van Osch, C.A. Schimmelpenninck, D.G. Norris,
M.J.A. Malessy, A. Galves and C.D. Vargas
|
Reduced functional connectivity within the primary motor cortex of
patients with brachial plexus injury
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This study aims at the effects of traumatic brachial plexus lesion with root
avulsions (BPA) upon the organization of the primary motor cortex (M1). Nine
right-handed patients with a right BPA in whom an intercostal to
musculocutaneous (ICN-MC) nerve transfer was performed had post-operative
resting state fRMI scanning. The analysis of empirical functional correlations
between neighboring voxels revealed faster decay as a function of distance in
the M1 region corresponding to the arm in BPA patients as compared to the
control group. No differences between the two groups were found in the face
area. We also investigated whether such larger decay in patients could be
attributed to a gray matter diminution in M1. Structural imaging analysis
showed no difference in gray matter density between groups. Our findings
suggest that the faster decay in neighboring functional correlations without
any gray matter diminution in BPA patients could be related to a reduced
activity in intrinsic horizontal connections in M1 responsible by upper limb
motor synergies.
|
[
{
"created": "Thu, 25 Jun 2015 20:07:26 GMT",
"version": "v1"
}
] |
2015-06-29
|
[
[
"Fraiman",
"D.",
""
],
[
"Miranda",
"M. F.",
""
],
[
"Erthal",
"F.",
""
],
[
"Buur",
"P. F.",
""
],
[
"Elschot",
"M.",
""
],
[
"Souza",
"L.",
""
],
[
"Rombouts",
"S. A. R. B.",
""
],
[
"van Osch",
"M. J. P.",
""
],
[
"Schimmelpenninck",
"C. A.",
""
],
[
"Norris",
"D. G.",
""
],
[
"Malessy",
"M. J. A.",
""
],
[
"Galves",
"A.",
""
],
[
"Vargas",
"C. D.",
""
]
] |
This study aims at the effects of traumatic brachial plexus lesion with root avulsions (BPA) upon the organization of the primary motor cortex (M1). Nine right-handed patients with a right BPA in whom an intercostal to musculocutaneous (ICN-MC) nerve transfer was performed had post-operative resting state fRMI scanning. The analysis of empirical functional correlations between neighboring voxels revealed faster decay as a function of distance in the M1 region corresponding to the arm in BPA patients as compared to the control group. No differences between the two groups were found in the face area. We also investigated whether such larger decay in patients could be attributed to a gray matter diminution in M1. Structural imaging analysis showed no difference in gray matter density between groups. Our findings suggest that the faster decay in neighboring functional correlations without any gray matter diminution in BPA patients could be related to a reduced activity in intrinsic horizontal connections in M1 responsible by upper limb motor synergies.
|
1809.04461
|
Vinayakumar R
|
Anu Vazhayil, Vinayakumar R and Soman KP
|
DeepProteomics: Protein family classification using Shallow and Deep
Networks
| null | null | null | null |
q-bio.QM cs.LG cs.NE stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The knowledge regarding the function of proteins is necessary as it gives a
clear picture of biological processes. Nevertheless, there are many protein
sequences found and added to the databases but lacks functional annotation. The
laboratory experiments take a considerable amount of time for annotation of the
sequences. This arises the need to use computational techniques to classify
proteins based on their functions. In our work, we have collected the data from
Swiss-Prot containing 40433 proteins which is grouped into 30 families. We pass
it to recurrent neural network(RNN), long short term memory(LSTM) and gated
recurrent unit(GRU) model and compare it by applying trigram with deep neural
network and shallow neural network on the same dataset. Through this approach,
we could achieve maximum of around 78% accuracy for the classification of
protein families.
|
[
{
"created": "Tue, 11 Sep 2018 17:48:01 GMT",
"version": "v1"
}
] |
2018-09-13
|
[
[
"Vazhayil",
"Anu",
""
],
[
"R",
"Vinayakumar",
""
],
[
"KP",
"Soman",
""
]
] |
The knowledge regarding the function of proteins is necessary as it gives a clear picture of biological processes. Nevertheless, there are many protein sequences found and added to the databases but lacks functional annotation. The laboratory experiments take a considerable amount of time for annotation of the sequences. This arises the need to use computational techniques to classify proteins based on their functions. In our work, we have collected the data from Swiss-Prot containing 40433 proteins which is grouped into 30 families. We pass it to recurrent neural network(RNN), long short term memory(LSTM) and gated recurrent unit(GRU) model and compare it by applying trigram with deep neural network and shallow neural network on the same dataset. Through this approach, we could achieve maximum of around 78% accuracy for the classification of protein families.
|
1512.04495
|
Dimiter Prodanov
|
Dimiter Prodanov and Jean Delbeke
|
A model of fractional-order diffusion in the glial scar
|
Figures excluded due to technical issues
| null | null | null |
q-bio.TO q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Implantation of neuroprosthetic electrodes induces a stereotypical state of
neuroinflammation, which is thought to be detrimental for the neurons
surrounding the electrode. Mechanisms of this type of neuroinflammation are
still not understood well. Recent experimental and theoretical results point
out possible role of the diffusion species in this process. The paper considers
a model of anomalous diffusion occurring in the glial scar around a chronic
implant in two simple geometries -- a separable rectilinear electrode and a
cylindrical electrode, which are solvable exactly. We describe a hypothetical
extended source of diffusing species and study its concentration profile in
steady-state conditions. Diffusion transport is assumed to obey a
fractional-order Fick law, which is derived from physically realistic
assumptions using a fractional calculus approach. The derived fractional-order
distribution morphs into regular order diffusion in the case of integer
fractional exponents. The model presented here demonstrates that accumulation
of diffusing species can occur and the scar properties (i.e. tortuosity,
fractional order, scar thickness) can influence such accumulation. The observed
shape of the concentration profile corresponds qualitatively with GFAP profiles
reported in the literature. The main difference with respect to the previous
studies is the explicit incorporation of the apparatus of fractional calculus
without assumption of an ad hoc tortuosity parameter. Intended application of
the approach is the study of diffusing substances in the glial scar after
implantation of neural prostheses, although the approach can be adapted to
other studies of diffusion in biological tissues, for example of biomolecules
or small drug molecules.
|
[
{
"created": "Mon, 14 Dec 2015 20:01:01 GMT",
"version": "v1"
}
] |
2015-12-15
|
[
[
"Prodanov",
"Dimiter",
""
],
[
"Delbeke",
"Jean",
""
]
] |
Implantation of neuroprosthetic electrodes induces a stereotypical state of neuroinflammation, which is thought to be detrimental for the neurons surrounding the electrode. Mechanisms of this type of neuroinflammation are still not understood well. Recent experimental and theoretical results point out possible role of the diffusion species in this process. The paper considers a model of anomalous diffusion occurring in the glial scar around a chronic implant in two simple geometries -- a separable rectilinear electrode and a cylindrical electrode, which are solvable exactly. We describe a hypothetical extended source of diffusing species and study its concentration profile in steady-state conditions. Diffusion transport is assumed to obey a fractional-order Fick law, which is derived from physically realistic assumptions using a fractional calculus approach. The derived fractional-order distribution morphs into regular order diffusion in the case of integer fractional exponents. The model presented here demonstrates that accumulation of diffusing species can occur and the scar properties (i.e. tortuosity, fractional order, scar thickness) can influence such accumulation. The observed shape of the concentration profile corresponds qualitatively with GFAP profiles reported in the literature. The main difference with respect to the previous studies is the explicit incorporation of the apparatus of fractional calculus without assumption of an ad hoc tortuosity parameter. Intended application of the approach is the study of diffusing substances in the glial scar after implantation of neural prostheses, although the approach can be adapted to other studies of diffusion in biological tissues, for example of biomolecules or small drug molecules.
|
0801.2302
|
Paolo Tieri
|
Paolo Tieri, Gastone C. Castellani, Claudio Franceschi
|
Towards an unifying perspective of the fundamental properties and
structural principles governing the immune system
|
3 pages, abstract of the poster and oral presentation at SBH2007
SysBioHealth Symposium, Systems Biology for Health, Milano, 17-19 October
2007
| null | null | null |
q-bio.OT
| null |
In the study of the basic properties observed in the immune system and, in a
broader view, in biological systems, several concepts have already been
mathematically formulated or treated in an analytical perspective, such as
degeneracy, robustness, noise, and bow tie architecture. These properties,
among others, seem to rule many aspects of the system functioning, and share
among themselvesseveral characteristics, intersecting each other, and often
becoming one the indivisible part of the other. According to Kitano, systems
biology needs solid theoretical and methodological foundation of principles and
properties, able to lead towards a unified perspective. An effort in unifying
the formalization and analysis of these principles can be now timely attempted.
|
[
{
"created": "Tue, 15 Jan 2008 14:05:56 GMT",
"version": "v1"
}
] |
2008-01-16
|
[
[
"Tieri",
"Paolo",
""
],
[
"Castellani",
"Gastone C.",
""
],
[
"Franceschi",
"Claudio",
""
]
] |
In the study of the basic properties observed in the immune system and, in a broader view, in biological systems, several concepts have already been mathematically formulated or treated in an analytical perspective, such as degeneracy, robustness, noise, and bow tie architecture. These properties, among others, seem to rule many aspects of the system functioning, and share among themselvesseveral characteristics, intersecting each other, and often becoming one the indivisible part of the other. According to Kitano, systems biology needs solid theoretical and methodological foundation of principles and properties, able to lead towards a unified perspective. An effort in unifying the formalization and analysis of these principles can be now timely attempted.
|
2301.04815
|
Hongsong Feng
|
Hongsong Feng, Rana Elladki, Jian Jiang, and Guo-Wei Wei
|
Machine-learning Analysis of Opioid Use Disorder Informed by MOR, DOR,
KOR, NOR and ZOR-Based Interactome Networks
| null | null | null | null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Opioid use disorder (OUD) continuously poses major public health challenges
and social implications worldwide with dramatic rise of opioid dependence
leading to potential abuse. Despite that a few pharmacological agents have been
approved for OUD treatment, the efficacy of said agents for OUD requires
further improvement in order to provide safer and more effective
pharmacological and psychosocial treatments. Preferable therapeutic treatments
of OUD rely on the advances in understanding the neurobiological mechanism of
opioid dependence. Proteins including mu, delta, kappa, nociceptin, and zeta
opioid receptors are the direct targets of opioids. Each receptor has a large
protein-protein interaction (PPI) network, that behaves differently when
subjected to various treatments, thus increasing the complexity in the drug
development process for an effective opioid addiction treatment. The report
below analyzes the work by presenting a PPI-network informed machine-learning
study of OUD. We have examined more than 500 proteins in the five opioid
receptor networks and subsequently collected 74 inhibitor datasets. Machine
learning models were constructed by pairing gradient boosting decision tree
(GBDT) algorithm with two advanced natural language processing (NLP)-based
molecular fingerprints. With these models, we systematically carried out
evaluations of screening and repurposing potential of drug candidates for four
opioid receptors. In addition, absorption, distribution, metabolism, excretion,
and toxicity (ADMET) properties were also considered in the screening of
potential drug candidates. Our study can be a valuable and promising tool of
pharmacological development for OUD treatments.
|
[
{
"created": "Thu, 12 Jan 2023 05:05:25 GMT",
"version": "v1"
}
] |
2023-01-13
|
[
[
"Feng",
"Hongsong",
""
],
[
"Elladki",
"Rana",
""
],
[
"Jiang",
"Jian",
""
],
[
"Wei",
"Guo-Wei",
""
]
] |
Opioid use disorder (OUD) continuously poses major public health challenges and social implications worldwide with dramatic rise of opioid dependence leading to potential abuse. Despite that a few pharmacological agents have been approved for OUD treatment, the efficacy of said agents for OUD requires further improvement in order to provide safer and more effective pharmacological and psychosocial treatments. Preferable therapeutic treatments of OUD rely on the advances in understanding the neurobiological mechanism of opioid dependence. Proteins including mu, delta, kappa, nociceptin, and zeta opioid receptors are the direct targets of opioids. Each receptor has a large protein-protein interaction (PPI) network, that behaves differently when subjected to various treatments, thus increasing the complexity in the drug development process for an effective opioid addiction treatment. The report below analyzes the work by presenting a PPI-network informed machine-learning study of OUD. We have examined more than 500 proteins in the five opioid receptor networks and subsequently collected 74 inhibitor datasets. Machine learning models were constructed by pairing gradient boosting decision tree (GBDT) algorithm with two advanced natural language processing (NLP)-based molecular fingerprints. With these models, we systematically carried out evaluations of screening and repurposing potential of drug candidates for four opioid receptors. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties were also considered in the screening of potential drug candidates. Our study can be a valuable and promising tool of pharmacological development for OUD treatments.
|
2111.04784
|
Zahra Nasiriavanaki
|
Roger B. H. Tootell and Zahra Nasiriavanaki, Baktash Babadi, Douglas
N. Greve, Shahin Nasr, Daphne J. Holt
|
Interdigitated Columnar Representation of Personal Space and Visual
Space in Human Parietal Cortex
|
19 pages, 10 figures and 1 table. Tootell and Nasiriavanaki share
joint first authorship
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Personal space (PS) is the distance that people prefer to maintain between
themselves and unfamiliar others. Interpersonal intrusion into a given persons
PS evokes discomfort, and an urge to move further apart. We hypothesized that
in parietal cortex: 1. PS processing involves a previously-described
threat-sensitive brain circuit, and 2. the spatial encoding of distance is
transformed accordingly, from purely sensory to PS-related. These hypotheses
were tested using 7T fMRI at high spatial resolution. In response to images of
different visual stimuli across a range of virtual distances, we found two
categories of distance encoding in functionally corresponding columns within
parietal cortex. First, PD (personal distance) columns responded selectively to
moving and stationary face images presented at virtual distances nearer (but
not further) than each subjects behaviorally-defined PS boundary. In the
majority of PD columns, BOLD response amplitudes increased monotonically and
nonlinearly with increasing virtual face proximity. In the remaining PD
columns, BOLD responses decreased with increasing proximity. These fMRI
response functions appear related to previously-reported variations in
subjective discomfort levels, and physiologic arousal, during intrusion into
but not beyond personal space. Secondly, DD (disparity distance) columns in
parietal cortex responded selectively to disparity-based near or far distances,
in random dot stimuli, like disparity-selective columns described previously in
occipital cortex. In parietal cortex, maps of DD columns were systematically
non-overlapping (interdigitated) with the PD columns. These results suggest
that the transformation of spatial information, from visual to higher-order,
may be computed in multiple small sites, rather than across a larger cortical
gradient, in parietal cortex.
|
[
{
"created": "Mon, 8 Nov 2021 19:43:15 GMT",
"version": "v1"
},
{
"created": "Tue, 25 Jan 2022 15:55:27 GMT",
"version": "v2"
},
{
"created": "Tue, 15 Mar 2022 03:53:56 GMT",
"version": "v3"
}
] |
2022-03-16
|
[
[
"Tootell",
"Roger B. H.",
""
],
[
"Nasiriavanaki",
"Zahra",
""
],
[
"Babadi",
"Baktash",
""
],
[
"Greve",
"Douglas N.",
""
],
[
"Nasr",
"Shahin",
""
],
[
"Holt",
"Daphne J.",
""
]
] |
Personal space (PS) is the distance that people prefer to maintain between themselves and unfamiliar others. Interpersonal intrusion into a given persons PS evokes discomfort, and an urge to move further apart. We hypothesized that in parietal cortex: 1. PS processing involves a previously-described threat-sensitive brain circuit, and 2. the spatial encoding of distance is transformed accordingly, from purely sensory to PS-related. These hypotheses were tested using 7T fMRI at high spatial resolution. In response to images of different visual stimuli across a range of virtual distances, we found two categories of distance encoding in functionally corresponding columns within parietal cortex. First, PD (personal distance) columns responded selectively to moving and stationary face images presented at virtual distances nearer (but not further) than each subjects behaviorally-defined PS boundary. In the majority of PD columns, BOLD response amplitudes increased monotonically and nonlinearly with increasing virtual face proximity. In the remaining PD columns, BOLD responses decreased with increasing proximity. These fMRI response functions appear related to previously-reported variations in subjective discomfort levels, and physiologic arousal, during intrusion into but not beyond personal space. Secondly, DD (disparity distance) columns in parietal cortex responded selectively to disparity-based near or far distances, in random dot stimuli, like disparity-selective columns described previously in occipital cortex. In parietal cortex, maps of DD columns were systematically non-overlapping (interdigitated) with the PD columns. These results suggest that the transformation of spatial information, from visual to higher-order, may be computed in multiple small sites, rather than across a larger cortical gradient, in parietal cortex.
|
2308.03406
|
Neta Maimon
|
Lior Molcho, Neta B. Maimon, Neomi Hezi, Talya Zeimer, Nathan
Intrator, Tanya Gurevich
|
Evaluation of Parkinsons disease with early diagnosis using
single-channel EEG features and auditory cognitive assessment
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by/4.0/
|
Parkinsons disease (PD) diagnosis is challenging due to subtle early clinical
signs. F-DOPA PET is commonly used for early PD diagnosis. We explore the
potential of machine-learning (ML) based EEG features extracted from
single-channel EEG during auditory cognitive assessment as a noninvasive,
low-cost support for PD diagnosis. The study included data collected from 32
participants who underwent an F-DOPA PET scan as part of their standard
treatment and 20 cognitively healthy controls. Participants performed an
auditory cognitive assessment recorded with Neurosteer EEG device. Data
processing involved wavelet-packet decomposition and ML. First, a prediction
model was developed to predict 1/3 of the undisclosed F-DOPA results. Then,
generalized linear mixed models were calculated to distinguish between PD and
non-PD subjects on the frequency bands and ML-based EEG features (A0 and L1)
previously associated with cognitive functions. The prediction model accurately
labeled patients with unrevealed scores as positive F-DOPA. Novel EEG feature
A0 and the Delta band showed significant separation between study groups, with
healthy controls exhibiting higher activity than PD patients. EEG feature L1
activity was significantly lower in resting state compared to high-cognitive
load. This effect was absent in the PD group, suggesting that lower activity in
resting state is lacking in PD patients. This study successfully demonstrated
the ability to separate patients with positive vs. negative F-DOPA PET results
with an easy-to-use single-channel EEG during an auditory cognitive assessment.
Future longitudinal studies should further explore the potential utility of
this tool for early PD diagnosis and as a potential biomarker in PD.
|
[
{
"created": "Mon, 7 Aug 2023 08:48:20 GMT",
"version": "v1"
}
] |
2023-08-08
|
[
[
"Molcho",
"Lior",
""
],
[
"Maimon",
"Neta B.",
""
],
[
"Hezi",
"Neomi",
""
],
[
"Zeimer",
"Talya",
""
],
[
"Intrator",
"Nathan",
""
],
[
"Gurevich",
"Tanya",
""
]
] |
Parkinsons disease (PD) diagnosis is challenging due to subtle early clinical signs. F-DOPA PET is commonly used for early PD diagnosis. We explore the potential of machine-learning (ML) based EEG features extracted from single-channel EEG during auditory cognitive assessment as a noninvasive, low-cost support for PD diagnosis. The study included data collected from 32 participants who underwent an F-DOPA PET scan as part of their standard treatment and 20 cognitively healthy controls. Participants performed an auditory cognitive assessment recorded with Neurosteer EEG device. Data processing involved wavelet-packet decomposition and ML. First, a prediction model was developed to predict 1/3 of the undisclosed F-DOPA results. Then, generalized linear mixed models were calculated to distinguish between PD and non-PD subjects on the frequency bands and ML-based EEG features (A0 and L1) previously associated with cognitive functions. The prediction model accurately labeled patients with unrevealed scores as positive F-DOPA. Novel EEG feature A0 and the Delta band showed significant separation between study groups, with healthy controls exhibiting higher activity than PD patients. EEG feature L1 activity was significantly lower in resting state compared to high-cognitive load. This effect was absent in the PD group, suggesting that lower activity in resting state is lacking in PD patients. This study successfully demonstrated the ability to separate patients with positive vs. negative F-DOPA PET results with an easy-to-use single-channel EEG during an auditory cognitive assessment. Future longitudinal studies should further explore the potential utility of this tool for early PD diagnosis and as a potential biomarker in PD.
|
1212.1323
|
David Saakian
|
David B. Saakian, Michael W. Deem, Chin Kun Hu
|
Finite population size effects in quasispecies models with single-peak
fitness landscape
|
7 pages, 1 figure
|
EPL, 98 (2012) 18001
|
10.1209/0295-5075/98/18001
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We consider finite population size effects for Crow-Kimura and Eigen
quasispecies models with single peak fitness landscape. We formulate accurately
the iteration procedure for the finite population models, then derive
Hamilton-Jacobi equation (HJE) to describe the dynamic of the probability
distribution. The steady state solution of HJE gives the variance of the mean
fitness. Our results are useful for understanding population sizes of virus in
which the infinite population models can give reliable results for the
biological evolution problems.
|
[
{
"created": "Thu, 6 Dec 2012 13:26:28 GMT",
"version": "v1"
}
] |
2015-06-12
|
[
[
"Saakian",
"David B.",
""
],
[
"Deem",
"Michael W.",
""
],
[
"Hu",
"Chin Kun",
""
]
] |
We consider finite population size effects for Crow-Kimura and Eigen quasispecies models with single peak fitness landscape. We formulate accurately the iteration procedure for the finite population models, then derive Hamilton-Jacobi equation (HJE) to describe the dynamic of the probability distribution. The steady state solution of HJE gives the variance of the mean fitness. Our results are useful for understanding population sizes of virus in which the infinite population models can give reliable results for the biological evolution problems.
|
2108.02706
|
K. Anton Feenstra
|
Halima Mouhib, Bas Stringer, Hugo van Ingen, Jose Gavald\'a-Garc\'ia,
Katharina Waury, Sanne Abeln, K. Anton Feenstra
|
Structure determination
|
This chapter is part of the book "Introduction to Protein Structural
Bioinformatics". The Preface arxiv:1801.09442 contains links to all the
(published) chapters
| null | null | null |
q-bio.BM
|
http://creativecommons.org/licenses/by/4.0/
|
While many good textbooks are available on Protein Structure, Molecular
Simulations, Thermodynamics and Bioinformatics methods in general, there is no
good introductory level book for the field of Structural Bioinformatics. This
book aims to give an introduction into Structural Bioinformatics, which is
where the previous topics meet to explore three dimensional protein structures
through computational analysis. We provide an overview of existing
computational techniques, to validate, simulate, predict and analyse protein
structures. More importantly, it will aim to provide practical knowledge about
how and when to use such techniques. We will consider proteins from three major
vantage points: Protein structure quantification, Protein structure prediction,
and Protein simulation & dynamics.
The main emphasis of this work is to provide a background on experimental
techniques for protein structure determination. The focus is set on X-ray
crystallography and Nuclear Magnetic Resonance spectroscopy (NMR), which are by
far the main methods used to determine the structure of soluble proteins. We
will also introduce cryogenic Electron Microscopy (cryo-EM) and electron
diffraction which are more suited to analyze membrane proteins and larger
protein complexes. At the end, more qualitative techniques are summarized that
are used to obtain insight on the overall structure and dynamics of proteins.
Note that this introduction to protein structure determination aims at
familiarizing the reader to different experimental techniques, their benefits
and bottlenecks, but that a thorough mathematical and technical description of
the concept is beyond the scope of this work.
|
[
{
"created": "Thu, 5 Aug 2021 16:16:10 GMT",
"version": "v1"
}
] |
2021-08-06
|
[
[
"Mouhib",
"Halima",
""
],
[
"Stringer",
"Bas",
""
],
[
"van Ingen",
"Hugo",
""
],
[
"Gavaldá-García",
"Jose",
""
],
[
"Waury",
"Katharina",
""
],
[
"Abeln",
"Sanne",
""
],
[
"Feenstra",
"K. Anton",
""
]
] |
While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. The main emphasis of this work is to provide a background on experimental techniques for protein structure determination. The focus is set on X-ray crystallography and Nuclear Magnetic Resonance spectroscopy (NMR), which are by far the main methods used to determine the structure of soluble proteins. We will also introduce cryogenic Electron Microscopy (cryo-EM) and electron diffraction which are more suited to analyze membrane proteins and larger protein complexes. At the end, more qualitative techniques are summarized that are used to obtain insight on the overall structure and dynamics of proteins. Note that this introduction to protein structure determination aims at familiarizing the reader to different experimental techniques, their benefits and bottlenecks, but that a thorough mathematical and technical description of the concept is beyond the scope of this work.
|
q-bio/0608014
|
Anders Eriksson
|
Anders Eriksson and Kristian Lindgren
|
The effect of finite population size on the evolutionary dynamics in
multi-person Prisoner's Dilemma
|
Accepted for publication in conference proceedings of ECCS'06
| null | null | null |
q-bio.PE
| null |
We study the influence of stochastic effects due to finite population size in
the evolutionary dynamics of populations interacting in the multi-person
Prisoner's Dilemma game. This paper is an extension of the investigation
presented in a recent paper [Eriksson and Lindgren (2005), J. Theor. Biol.
232(3), 399]. One of the main results of the previous study is that there are
modes of dynamic behaviour, such as limit cycles and fixed points, that are
maintained due to a non-zero mutation level, resulting in a significantly
higher level of cooperation than was reported in earlier studies. In the
present study, we investigate two mechanisms in the evolutionary dynamics for
finite populations: (i) a stochastic model of the mutation process, and (ii) a
stochastic model of the selection process. The most evident effect comes from
the second extension, where we find that a previously stable limit cycle is
replaced by a trajectory that to a large extent is close to a fixed point that
is stable in the deterministic model. The effect is strong even when population
size is as large as 10,000. The effect of the first mechanism is less
pronounced, and an argument for this difference is given.
|
[
{
"created": "Mon, 7 Aug 2006 14:56:00 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Eriksson",
"Anders",
""
],
[
"Lindgren",
"Kristian",
""
]
] |
We study the influence of stochastic effects due to finite population size in the evolutionary dynamics of populations interacting in the multi-person Prisoner's Dilemma game. This paper is an extension of the investigation presented in a recent paper [Eriksson and Lindgren (2005), J. Theor. Biol. 232(3), 399]. One of the main results of the previous study is that there are modes of dynamic behaviour, such as limit cycles and fixed points, that are maintained due to a non-zero mutation level, resulting in a significantly higher level of cooperation than was reported in earlier studies. In the present study, we investigate two mechanisms in the evolutionary dynamics for finite populations: (i) a stochastic model of the mutation process, and (ii) a stochastic model of the selection process. The most evident effect comes from the second extension, where we find that a previously stable limit cycle is replaced by a trajectory that to a large extent is close to a fixed point that is stable in the deterministic model. The effect is strong even when population size is as large as 10,000. The effect of the first mechanism is less pronounced, and an argument for this difference is given.
|
1903.09535
|
Laura Murphy
|
Laura Murphy, Anotida Madzvamuse
|
A moving grid finite element method applied to a mechanobiochemical
model for 3D cell migration
| null | null | null | null |
q-bio.CB math.NA
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This work presents the development, analysis and numerical simulations of a
biophysical model for 3D cell deformation and movement, which couples
biochemical reactions and biomechanical forces. We propose a mechanobiochemical
model which considers the actin filament network as a viscoelastic and
contractile gel. The mechanical properties are modelled by a force balancing
equation for the displacements, the pressure and concentration forces are
driven by actin and myosin dynamics, and these are in turn modelled by a system
of reaction-diffusion equations on a moving cell domain. The biophysical model
consists of highly non-linear partial differential equations whose analytical
solutions are intractable. To obtain approximate solutions to the model system,
we employ the moving grid finite element method. The numerical results are
supported by linear stability theoretical results close to bifurcation points
during the early stages of cell migration. Numerical simulations exhibited show
both simple and complex cell deformations in 3-dimensions that include cell
expansion, cell protrusion and cell contraction. The computational framework
presented here sets a strong foundation that allows to study more complex and
experimentally driven reaction-kinetics involving actin, myosin and other
molecular species that play an important role in cell movement and deformation.
|
[
{
"created": "Fri, 22 Mar 2019 14:48:14 GMT",
"version": "v1"
}
] |
2019-03-25
|
[
[
"Murphy",
"Laura",
""
],
[
"Madzvamuse",
"Anotida",
""
]
] |
This work presents the development, analysis and numerical simulations of a biophysical model for 3D cell deformation and movement, which couples biochemical reactions and biomechanical forces. We propose a mechanobiochemical model which considers the actin filament network as a viscoelastic and contractile gel. The mechanical properties are modelled by a force balancing equation for the displacements, the pressure and concentration forces are driven by actin and myosin dynamics, and these are in turn modelled by a system of reaction-diffusion equations on a moving cell domain. The biophysical model consists of highly non-linear partial differential equations whose analytical solutions are intractable. To obtain approximate solutions to the model system, we employ the moving grid finite element method. The numerical results are supported by linear stability theoretical results close to bifurcation points during the early stages of cell migration. Numerical simulations exhibited show both simple and complex cell deformations in 3-dimensions that include cell expansion, cell protrusion and cell contraction. The computational framework presented here sets a strong foundation that allows to study more complex and experimentally driven reaction-kinetics involving actin, myosin and other molecular species that play an important role in cell movement and deformation.
|
1712.04987
|
Kevin O'Regan
|
Aurora Rizza, Alexander V. Terekhov, Guglielmo Montone, Marta Olivetti
Belardinelli, J. Kevin O'Regan
|
Why early tactile speech aids may have failed: no perceptual integration
of tactile and auditory signals
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Tactile speech aids, though extensively studied in the 1980s and 90s, never
became a commercial success. A hypothesis to explain this failure might be that
it is difficult to obtain true perceptual integration of a tactile signal with
information from auditory speech: exploitation of tactile cues from a tactile
aid might require cognitive effort and so prevent speech understanding at the
high rates typical of everyday speech. To test this hypothesis, we attempted to
create true perceptual integration of tactile with auditory information in what
might be considered the simplest situation encountered by a hearing-impaired
listener. We created an auditory continuum between the syllables BA and VA, and
trained participants to associate BA to one tactile stimulus VA to another
tactile stimulus. After training, we tested if auditory discrimination along
the continuum between the two syllables could be biased by incongruent tactile
stimulation. We found that such a bias occurred only when the tactile stimulus
was above its previously measured tactile discrimination threshold. Such a
pattern is compatible with the idea that the effect is due to a cognitive or
decisional strategy, rather than to truly perceptual integration. We therefore
ran a further study, where we created a tactile version of the McGurk effect.
We extensively trained two Subjects over six days to associate four recorded
auditory syllables with four corresponding apparent motion tactile patterns. In
a subsequent test, we presented stimulation that was either congruent or
incongruent with the learnt association, and asked Subjects to report the
syllable they perceived. We found no analog to the McGurk effect. These
findings strengthen our hypothesis according to which tactile aids failed
because integration of tactile cues with auditory speech occurred at a
cognitive or decisional level, rather than truly at a perceptual level
|
[
{
"created": "Tue, 28 Nov 2017 09:30:34 GMT",
"version": "v1"
}
] |
2017-12-15
|
[
[
"Rizza",
"Aurora",
""
],
[
"Terekhov",
"Alexander V.",
""
],
[
"Montone",
"Guglielmo",
""
],
[
"Belardinelli",
"Marta Olivetti",
""
],
[
"O'Regan",
"J. Kevin",
""
]
] |
Tactile speech aids, though extensively studied in the 1980s and 90s, never became a commercial success. A hypothesis to explain this failure might be that it is difficult to obtain true perceptual integration of a tactile signal with information from auditory speech: exploitation of tactile cues from a tactile aid might require cognitive effort and so prevent speech understanding at the high rates typical of everyday speech. To test this hypothesis, we attempted to create true perceptual integration of tactile with auditory information in what might be considered the simplest situation encountered by a hearing-impaired listener. We created an auditory continuum between the syllables BA and VA, and trained participants to associate BA to one tactile stimulus VA to another tactile stimulus. After training, we tested if auditory discrimination along the continuum between the two syllables could be biased by incongruent tactile stimulation. We found that such a bias occurred only when the tactile stimulus was above its previously measured tactile discrimination threshold. Such a pattern is compatible with the idea that the effect is due to a cognitive or decisional strategy, rather than to truly perceptual integration. We therefore ran a further study, where we created a tactile version of the McGurk effect. We extensively trained two Subjects over six days to associate four recorded auditory syllables with four corresponding apparent motion tactile patterns. In a subsequent test, we presented stimulation that was either congruent or incongruent with the learnt association, and asked Subjects to report the syllable they perceived. We found no analog to the McGurk effect. These findings strengthen our hypothesis according to which tactile aids failed because integration of tactile cues with auditory speech occurred at a cognitive or decisional level, rather than truly at a perceptual level
|
2005.01491
|
Elmira Jalilian
|
Elmira Jalilian, William Raimes
|
Transcriptional profiling reveals fundamental differences in iPS-derived
progenitors of endothelial cells (PECs) versus adult circulating EPCs
| null | null | null | null |
q-bio.CB q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
There are a number of different stem cell sources that have the potential to
be used as therapeutics in vascular degenerative diseases. On the one hand,
there are so called endothelial progenitor cells (EPCs), which are typically
derived from adult blood. They carry the marker CD34, but the true nature and
definition of EPCs is still controversial. On the other hand, there are
embryonic precursors of endothelial cells (PECs), which also express CD34, and
can be differentiated from embryonic stem cells (ESCs) or induced pluripotent
stem cells (iPSCs) in vitro. In this study, it was aimed to compare these two
different CD34 positive cell populations by full genome transcriptional
profiling (RNAseq). To this end, we firstly optimised a PEC differentiation
protocol and found that vascular endothelial growth factor (VEGF) is critical
for the transition of cells from mesodermal precursors to PECs. Additionally,
principal component analysis (PCA) of RNAseq data showed that blood-derived
EPCs clustered far from iPS-derived PECs which illustrates these populations
are fundamentally different. This data will be useful to better define these
cell populations and facilitating the translation of regenerative approaches in
this field as well as providing potentially novel diagnostic tools.
|
[
{
"created": "Mon, 4 May 2020 13:47:25 GMT",
"version": "v1"
}
] |
2020-05-05
|
[
[
"Jalilian",
"Elmira",
""
],
[
"Raimes",
"William",
""
]
] |
There are a number of different stem cell sources that have the potential to be used as therapeutics in vascular degenerative diseases. On the one hand, there are so called endothelial progenitor cells (EPCs), which are typically derived from adult blood. They carry the marker CD34, but the true nature and definition of EPCs is still controversial. On the other hand, there are embryonic precursors of endothelial cells (PECs), which also express CD34, and can be differentiated from embryonic stem cells (ESCs) or induced pluripotent stem cells (iPSCs) in vitro. In this study, it was aimed to compare these two different CD34 positive cell populations by full genome transcriptional profiling (RNAseq). To this end, we firstly optimised a PEC differentiation protocol and found that vascular endothelial growth factor (VEGF) is critical for the transition of cells from mesodermal precursors to PECs. Additionally, principal component analysis (PCA) of RNAseq data showed that blood-derived EPCs clustered far from iPS-derived PECs which illustrates these populations are fundamentally different. This data will be useful to better define these cell populations and facilitating the translation of regenerative approaches in this field as well as providing potentially novel diagnostic tools.
|
1104.2261
|
Antti Niemi
|
Martin Lundgren, Antti J. Niemi and Fan Sha
|
On universal aspects of the left-handed helix region
|
13 figures
| null | null | null |
q-bio.BM cond-mat.soft physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We inspect the geometry of proteins by identifying their backbones as framed
polygons. We find that the left-handed helix region of the Ramachandran map for
non-glycyl residues corresponds to an isolated and highly localized sector in
the orientation of the $C_\beta$ carbons, when viewed in a Frenet frame that is
centered at the corresponding $C_\alpha$ carbons. We show that this
localization in the orientation persists to $C_\gamma$ and $C_\delta$ carbons.
Furthermore, when we extend our analysis to the neighboring residues we
conclude that the left-handed helix region reflects a very regular and
apparently residue independent collective interplay of at least seven
consecutive amino acids.
|
[
{
"created": "Tue, 12 Apr 2011 16:25:49 GMT",
"version": "v1"
}
] |
2011-04-13
|
[
[
"Lundgren",
"Martin",
""
],
[
"Niemi",
"Antti J.",
""
],
[
"Sha",
"Fan",
""
]
] |
We inspect the geometry of proteins by identifying their backbones as framed polygons. We find that the left-handed helix region of the Ramachandran map for non-glycyl residues corresponds to an isolated and highly localized sector in the orientation of the $C_\beta$ carbons, when viewed in a Frenet frame that is centered at the corresponding $C_\alpha$ carbons. We show that this localization in the orientation persists to $C_\gamma$ and $C_\delta$ carbons. Furthermore, when we extend our analysis to the neighboring residues we conclude that the left-handed helix region reflects a very regular and apparently residue independent collective interplay of at least seven consecutive amino acids.
|
2203.13043
|
Yannik Sch\"alte
|
Yannik Sch\"alte, Emmanuel Klinger, Emad Alamoudi, Jan Hasenauer
|
pyABC: Efficient and robust easy-to-use approximate Bayesian computation
|
8 pages, 1 figure
| null | null | null |
q-bio.QM stat.CO
|
http://creativecommons.org/licenses/by/4.0/
|
The Python package pyABC provides a framework for approximate Bayesian
computation (ABC), a likelihood-free parameter inference method popular in many
research areas. At its core, it implements a sequential Monte-Carlo (SMC)
scheme, with various algorithms to adapt to the problem structure and
automatically tune hyperparameters. To scale to computationally expensive
problems, it provides efficient parallelization strategies for multi-core and
distributed systems. The package is highly modular and designed to be easily
usable. In this major update to pyABC, we implement several advanced algorithms
that facilitate efficient and robust inference on a wide range of data and
model types. In particular, we implement algorithms to account for noise, to
adaptively scale-normalize distance metrics, to robustly handle data outliers,
to elucidate informative data points via regression models, to circumvent
summary statistics via optimal transport based distances, and to avoid local
optima in acceptance threshold sequences by predicting acceptance rate curves.
Further, we provide, besides previously existing support of Python and R,
interfaces in particular to the Julia language, the COPASI simulator, and the
PEtab standard.
|
[
{
"created": "Thu, 24 Mar 2022 12:44:21 GMT",
"version": "v1"
}
] |
2022-03-25
|
[
[
"Schälte",
"Yannik",
""
],
[
"Klinger",
"Emmanuel",
""
],
[
"Alamoudi",
"Emad",
""
],
[
"Hasenauer",
"Jan",
""
]
] |
The Python package pyABC provides a framework for approximate Bayesian computation (ABC), a likelihood-free parameter inference method popular in many research areas. At its core, it implements a sequential Monte-Carlo (SMC) scheme, with various algorithms to adapt to the problem structure and automatically tune hyperparameters. To scale to computationally expensive problems, it provides efficient parallelization strategies for multi-core and distributed systems. The package is highly modular and designed to be easily usable. In this major update to pyABC, we implement several advanced algorithms that facilitate efficient and robust inference on a wide range of data and model types. In particular, we implement algorithms to account for noise, to adaptively scale-normalize distance metrics, to robustly handle data outliers, to elucidate informative data points via regression models, to circumvent summary statistics via optimal transport based distances, and to avoid local optima in acceptance threshold sequences by predicting acceptance rate curves. Further, we provide, besides previously existing support of Python and R, interfaces in particular to the Julia language, the COPASI simulator, and the PEtab standard.
|
1803.11559
|
Eve Armstrong
|
Eve Armstrong
|
Colonel Mustard in the Aviary with the Candlestick: a limit cycle
attractor transitions to a stable focus via supercritical Andronov-Hopf
bifurcation
|
5 figures, 8 pages
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We establish the means by which Mr. Boddy came to transition from a stable
trajectory within the global phase space of Philadelphia, Pennsylvania to a
stable point on the cement floor of an aviary near the west bank of the
Schuylkill River. There exist no documented murder motives, and so the
dynamical interaction leading to the crime must be reconstructed from
circumstantial data. Our investigation proceeds in two stages. First we take an
audio stream recorded within the aviary near the time of death to identify the
local embedding dimension, thereby enumerating the suspects. Second, we
characterize Mr. Boddy's pre- and post-mortem behavior in the phase space in
terms of an attractor that undergoes an abrupt change in stability. A
supercritical Andronov-Hopf bifurcation can explain this transition. Then we
uniquely identify the murderer. Finally, we note long-term plans to construct
an underlying dynamical model capable of predicting the stability of equilibria
in different parameter regimes, in the event that Mr. Boddy is ever murdered
again.
|
[
{
"created": "Sun, 1 Apr 2018 18:22:01 GMT",
"version": "v1"
},
{
"created": "Wed, 11 Jul 2018 19:34:24 GMT",
"version": "v2"
},
{
"created": "Wed, 25 Jul 2018 23:50:15 GMT",
"version": "v3"
}
] |
2018-07-27
|
[
[
"Armstrong",
"Eve",
""
]
] |
We establish the means by which Mr. Boddy came to transition from a stable trajectory within the global phase space of Philadelphia, Pennsylvania to a stable point on the cement floor of an aviary near the west bank of the Schuylkill River. There exist no documented murder motives, and so the dynamical interaction leading to the crime must be reconstructed from circumstantial data. Our investigation proceeds in two stages. First we take an audio stream recorded within the aviary near the time of death to identify the local embedding dimension, thereby enumerating the suspects. Second, we characterize Mr. Boddy's pre- and post-mortem behavior in the phase space in terms of an attractor that undergoes an abrupt change in stability. A supercritical Andronov-Hopf bifurcation can explain this transition. Then we uniquely identify the murderer. Finally, we note long-term plans to construct an underlying dynamical model capable of predicting the stability of equilibria in different parameter regimes, in the event that Mr. Boddy is ever murdered again.
|
1702.04088
|
Andreas Gunawan
|
Andreas Gunawan
|
Solving Tree Containment Problem for Reticulation-visible Networks with
Optimal Running Time
| null | null | null | null |
q-bio.PE cs.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Tree containment problem is a fundamental problem in phylogenetic study, as
it is used to verify a network model. It asks whether a given network contain a
subtree that resembles a binary tree. The problem is NP-complete in general,
even in the class of binary network. Recently, it was proven to be solvable in
cubic time, and later in quadratic time for the class of general reticulation
visible networks. In this paper, we further improve the time complexity into
linear time.
|
[
{
"created": "Tue, 14 Feb 2017 06:15:28 GMT",
"version": "v1"
}
] |
2017-02-15
|
[
[
"Gunawan",
"Andreas",
""
]
] |
Tree containment problem is a fundamental problem in phylogenetic study, as it is used to verify a network model. It asks whether a given network contain a subtree that resembles a binary tree. The problem is NP-complete in general, even in the class of binary network. Recently, it was proven to be solvable in cubic time, and later in quadratic time for the class of general reticulation visible networks. In this paper, we further improve the time complexity into linear time.
|
1802.01980
|
Jingjing Xu
|
Shengyong Xu, Jingjing Xu and Rujun Dai
|
Layered structure and leveled function of a human brain
| null | null | null | null |
q-bio.NC physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The anatomically layered structure of a human brain results in leveled
functions. In all these levels of different functions, comparison, feedback and
imitation are the universal and crucial mechanisms. Languages, symbols and
tools play key roles in the development of human brain and entire civilization.
|
[
{
"created": "Sun, 4 Feb 2018 05:58:42 GMT",
"version": "v1"
}
] |
2018-02-07
|
[
[
"Xu",
"Shengyong",
""
],
[
"Xu",
"Jingjing",
""
],
[
"Dai",
"Rujun",
""
]
] |
The anatomically layered structure of a human brain results in leveled functions. In all these levels of different functions, comparison, feedback and imitation are the universal and crucial mechanisms. Languages, symbols and tools play key roles in the development of human brain and entire civilization.
|
1303.5785
|
Dan DeBlasio
|
Dan DeBlasio and Jennifer Wiscaver
|
SICLE: A high-throughput tool for extracting evolutionary relationships
from phylogenetic trees
|
8 pages, 4 figures in journal submission format
| null |
10.7717/peerj.2359
| null |
q-bio.GN
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
We present the phylogeny analysis software SICLE (Sister Clade Extractor), an
easy-to-use, high- throughput tool to describe the nearest neighbors to a node
of interest in a phylogenetic tree as well as the support value for the
relationship. The application is a command line utility that can be embedded
into a phylogenetic analysis pipeline or can be used as a subroutine within
another C++ program. As a test case, we applied this new tool to the published
phylome of Salinibacter ruber, a species of halophilic Bacteriodetes,
identifying 13 unique sister relationships to S. ruber across the 4589 gene
phylogenies. S. ruber grouped with bacteria, most often other Bacteriodetes, in
the majority of phylogenies, but 91 phylogenies showed a branch-supported
sister association between S. ruber and Archaea, an evolutionarily intriguing
relationship indicative of horizontal gene transfer. This test case
demonstrates how SICLE makes it possible to summarize the phylogenetic
information produced by automated phylogenetic pipelines to rapidly identify
and quantify the possible evolutionary relationships that merit further
investigation. SICLE is available for free for noncommercial use at
http://eebweb.arizona.edu/sicle/.
|
[
{
"created": "Fri, 22 Mar 2013 22:07:04 GMT",
"version": "v1"
},
{
"created": "Wed, 15 Jun 2016 20:06:29 GMT",
"version": "v2"
},
{
"created": "Fri, 17 Jun 2016 00:42:43 GMT",
"version": "v3"
}
] |
2016-08-24
|
[
[
"DeBlasio",
"Dan",
""
],
[
"Wiscaver",
"Jennifer",
""
]
] |
We present the phylogeny analysis software SICLE (Sister Clade Extractor), an easy-to-use, high- throughput tool to describe the nearest neighbors to a node of interest in a phylogenetic tree as well as the support value for the relationship. The application is a command line utility that can be embedded into a phylogenetic analysis pipeline or can be used as a subroutine within another C++ program. As a test case, we applied this new tool to the published phylome of Salinibacter ruber, a species of halophilic Bacteriodetes, identifying 13 unique sister relationships to S. ruber across the 4589 gene phylogenies. S. ruber grouped with bacteria, most often other Bacteriodetes, in the majority of phylogenies, but 91 phylogenies showed a branch-supported sister association between S. ruber and Archaea, an evolutionarily intriguing relationship indicative of horizontal gene transfer. This test case demonstrates how SICLE makes it possible to summarize the phylogenetic information produced by automated phylogenetic pipelines to rapidly identify and quantify the possible evolutionary relationships that merit further investigation. SICLE is available for free for noncommercial use at http://eebweb.arizona.edu/sicle/.
|
1301.2397
|
Sepehr Ehsani
|
Sepehr Ehsani
|
Macro-trends in research on the central dogma of molecular biology
|
9 pages, 2 figures, 1 supplementary table, 3 supplementary figures
| null | null | null |
q-bio.QM cs.DL
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The central dogma of molecular biology, formulated more than five decades
ago, compartmentalized information exchange in the cell into the DNA, RNA and
protein domains. This formalization has served as an implicit thematic
distinguisher for cell biological research ever since. However, a clear account
of the distribution of research across this formalization over time does not
exist. Abstracts of >3.5 million publications focusing on the cell from 1975 to
2011 were analyzed for the frequency of 100 single-word DNA-, RNA- and
protein-centric search terms and amalgamated to produce domain- and
subdomain-specific trends. A preponderance of protein- over DNA- and in turn
over RNA-centric terms as a percentage of the total word count is evident until
the early 1990s, at which point the trends for protein and DNA begin to
coalesce while RNA percentages remain relatively unchanged. This term-based
census provides a yearly snapshot of the distribution of research interests
across the three domains of the central dogma of molecular biology. A frequency
chart of the most dominantly-studied elements of the periodic table is provided
as an addendum.
|
[
{
"created": "Fri, 11 Jan 2013 07:00:57 GMT",
"version": "v1"
},
{
"created": "Mon, 7 Oct 2013 22:18:25 GMT",
"version": "v2"
}
] |
2013-10-09
|
[
[
"Ehsani",
"Sepehr",
""
]
] |
The central dogma of molecular biology, formulated more than five decades ago, compartmentalized information exchange in the cell into the DNA, RNA and protein domains. This formalization has served as an implicit thematic distinguisher for cell biological research ever since. However, a clear account of the distribution of research across this formalization over time does not exist. Abstracts of >3.5 million publications focusing on the cell from 1975 to 2011 were analyzed for the frequency of 100 single-word DNA-, RNA- and protein-centric search terms and amalgamated to produce domain- and subdomain-specific trends. A preponderance of protein- over DNA- and in turn over RNA-centric terms as a percentage of the total word count is evident until the early 1990s, at which point the trends for protein and DNA begin to coalesce while RNA percentages remain relatively unchanged. This term-based census provides a yearly snapshot of the distribution of research interests across the three domains of the central dogma of molecular biology. A frequency chart of the most dominantly-studied elements of the periodic table is provided as an addendum.
|
2112.01081
|
Santiago Rivera
|
Pauline Zipfel (CERMN), Christophe Rochais (CERMN), K\'evin Baranger
(INP), Santiago Rivera (INP), Patrick Dallemagne (CERMN)
|
Matrix metalloproteinases as new targets in Alzheimer's disease:
Opportunities and Challenges
| null |
Journal of Medicinal Chemistry, American Chemical Society, 2020
| null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Although matrix metalloproteinases (MMPs) are implicated in the regulation of
numerous physiological processes, evidences of their pathological roles have
also been obtained in the last decades, making MMPs attractive therapeutic
targets for several diseases. Recent discoveries of their involvement in
central nervous system (CNS) disorders, and in particular in Alzheimer's
disease (AD), have paved the way to consider MMP modulators as promising
therapeutic strategies. Over the past few decades, diverse approaches have been
undertaken in the design of
|
[
{
"created": "Thu, 2 Dec 2021 09:49:20 GMT",
"version": "v1"
}
] |
2021-12-03
|
[
[
"Zipfel",
"Pauline",
"",
"CERMN"
],
[
"Rochais",
"Christophe",
"",
"CERMN"
],
[
"Baranger",
"Kévin",
"",
"INP"
],
[
"Rivera",
"Santiago",
"",
"INP"
],
[
"Dallemagne",
"Patrick",
"",
"CERMN"
]
] |
Although matrix metalloproteinases (MMPs) are implicated in the regulation of numerous physiological processes, evidences of their pathological roles have also been obtained in the last decades, making MMPs attractive therapeutic targets for several diseases. Recent discoveries of their involvement in central nervous system (CNS) disorders, and in particular in Alzheimer's disease (AD), have paved the way to consider MMP modulators as promising therapeutic strategies. Over the past few decades, diverse approaches have been undertaken in the design of
|
2308.00298
|
Hyunjoong Kim
|
Hyunjoong Kim, Yoichiro Mori, Joshua B Plotkin
|
Finite population effects on optimal communication for social foragers
| null | null | null | null |
q-bio.PE math.PR physics.bio-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Foraging is crucial for animals to survive. Many species forage in groups, as
individuals communicate to share information about the location of available
resources. For example, eusocial foragers, such as honey bees and many ants,
recruit members from their central hive or nest to a known foraging site.
However, the optimal level of communication and recruitment depends on the
overall group size, the distribution of available resources, and the extent of
interference between multiple individuals attempting to forage from a site. In
this paper, we develop a discrete-time Markov chain model of eusocial foragers,
who communicate information with a certain probability. We compare the
stochastic model and its corresponding infinite-population limit. We find that
foraging efficiency tapers off when recruitment probability is too high -- a
phenomenon that does not occur in the infinite-population model, even though it
occurs for any finite population size. The marginal inefficiency at high
recruitment probability increases as the population increases, similar to a
boundary layer. In particular, we prove there is a significant gap between the
foraging efficiency of finite and infinite population models in the extreme
case of complete communication. We also analyze this phenomenon by
approximating the stationary distribution of foragers over sites in terms of
mean escape times from multiple quasi-steady states. We conclude that for any
finite group of foragers, an individual who has found a resource should only
sometimes recruit others to the same resource. We discuss the relationship
between our analysis and multi-agent multi-arm bandit problems.
|
[
{
"created": "Tue, 1 Aug 2023 05:39:49 GMT",
"version": "v1"
}
] |
2023-08-02
|
[
[
"Kim",
"Hyunjoong",
""
],
[
"Mori",
"Yoichiro",
""
],
[
"Plotkin",
"Joshua B",
""
]
] |
Foraging is crucial for animals to survive. Many species forage in groups, as individuals communicate to share information about the location of available resources. For example, eusocial foragers, such as honey bees and many ants, recruit members from their central hive or nest to a known foraging site. However, the optimal level of communication and recruitment depends on the overall group size, the distribution of available resources, and the extent of interference between multiple individuals attempting to forage from a site. In this paper, we develop a discrete-time Markov chain model of eusocial foragers, who communicate information with a certain probability. We compare the stochastic model and its corresponding infinite-population limit. We find that foraging efficiency tapers off when recruitment probability is too high -- a phenomenon that does not occur in the infinite-population model, even though it occurs for any finite population size. The marginal inefficiency at high recruitment probability increases as the population increases, similar to a boundary layer. In particular, we prove there is a significant gap between the foraging efficiency of finite and infinite population models in the extreme case of complete communication. We also analyze this phenomenon by approximating the stationary distribution of foragers over sites in terms of mean escape times from multiple quasi-steady states. We conclude that for any finite group of foragers, an individual who has found a resource should only sometimes recruit others to the same resource. We discuss the relationship between our analysis and multi-agent multi-arm bandit problems.
|
1810.00501
|
Rohan Maddamsetti
|
Rohan Maddamsetti and Jacob Bower-Bir
|
Parallels and promising directions in the study of genetic, cultural,
and moral evolution
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Experimental evolution has yielded surprising insights into human history and
evolution by shedding light on the roles of chance and contingency in history
and evolution, and on the deep evolutionary roots of cooperation, conflict and
kin discrimination. We argue that an interesting research direction would be to
develop computational and experimental systems for studying evolutionary
processes that involve multiple layers of inheritance (such as genes,
epigenetic inheritance, language, and culture) and feedbacks (such as
gene-culture coevolution and mate choice) as well as open-ended niche
construction---all of which are important in human history and evolution. Such
systems would also be a clear way to motivate evolution and computation to
scholars and students across diverse cultural and socioeconomic backgrounds, as
well as to scholars and students in the social sciences and humanities. In
principle, computational models of cultural evolution could be compared to
data, given that large-scale datasets already exist for tracking cultural
change in real-time. Thus, experimental evolution, as a laboratory and
computational science, is poised to grow as an educational tool for people to
question and study where we come from, why we believe what we believe, and
where we as a species may be headed.
|
[
{
"created": "Mon, 1 Oct 2018 01:55:38 GMT",
"version": "v1"
}
] |
2018-10-02
|
[
[
"Maddamsetti",
"Rohan",
""
],
[
"Bower-Bir",
"Jacob",
""
]
] |
Experimental evolution has yielded surprising insights into human history and evolution by shedding light on the roles of chance and contingency in history and evolution, and on the deep evolutionary roots of cooperation, conflict and kin discrimination. We argue that an interesting research direction would be to develop computational and experimental systems for studying evolutionary processes that involve multiple layers of inheritance (such as genes, epigenetic inheritance, language, and culture) and feedbacks (such as gene-culture coevolution and mate choice) as well as open-ended niche construction---all of which are important in human history and evolution. Such systems would also be a clear way to motivate evolution and computation to scholars and students across diverse cultural and socioeconomic backgrounds, as well as to scholars and students in the social sciences and humanities. In principle, computational models of cultural evolution could be compared to data, given that large-scale datasets already exist for tracking cultural change in real-time. Thus, experimental evolution, as a laboratory and computational science, is poised to grow as an educational tool for people to question and study where we come from, why we believe what we believe, and where we as a species may be headed.
|
1406.1391
|
Donald Forsdyke Dr.
|
Donald R. Forsdyke
|
'A Vehicle of Symbols and Nothing More.' George Romanes, Theory of Mind,
Information, and Samuel Butler
|
Accepted for publication in History of Psychiatry. 31 pages including
3 footnotes. Based on a lecture given at Santa Clara University, February
28th 2014, at a Bannan Institute Symposium on 'Science and Seeking:
Rethinking the God Question in the Lab, Cosmos, and Classroom.' - See more at
either http://www.youtube.com/watch?v=a3yNbTUCPd4 or
http://www.youtube.com/watch?v=ezcdIrR9r-w
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Today's 'theory of mind' (ToM) concept is rooted in the distinction of
nineteenth century philosopher William Clifford between 'objects' that can be
directly perceived, and 'ejects,' such as the mind of another person, which are
inferred from one's subjective knowledge of one's own mind. A founder, with
Charles Darwin, of the discipline of comparative psychology, George Romanes
considered the minds of animals as ejects, an idea that could be generalized to
'society as eject' and, ultimately, 'the world as an eject' - mind in the
universe. Yet, Romanes and Clifford only vaguely connected mind with the
abstraction we call 'information,' which needs 'a vehicle of symbols' - a
material transporting medium. However, Samuel Butler was able to address, in
informational terms depleted of theological trappings, both organic evolution
and mind in the universe. This view harmonizes with insights arising from
modern DNA research, the relative immortality of 'selfish' genes, and some
startling recent developments in brain research.
|
[
{
"created": "Wed, 4 Jun 2014 03:04:49 GMT",
"version": "v1"
},
{
"created": "Thu, 13 Nov 2014 22:19:37 GMT",
"version": "v2"
}
] |
2014-11-17
|
[
[
"Forsdyke",
"Donald R.",
""
]
] |
Today's 'theory of mind' (ToM) concept is rooted in the distinction of nineteenth century philosopher William Clifford between 'objects' that can be directly perceived, and 'ejects,' such as the mind of another person, which are inferred from one's subjective knowledge of one's own mind. A founder, with Charles Darwin, of the discipline of comparative psychology, George Romanes considered the minds of animals as ejects, an idea that could be generalized to 'society as eject' and, ultimately, 'the world as an eject' - mind in the universe. Yet, Romanes and Clifford only vaguely connected mind with the abstraction we call 'information,' which needs 'a vehicle of symbols' - a material transporting medium. However, Samuel Butler was able to address, in informational terms depleted of theological trappings, both organic evolution and mind in the universe. This view harmonizes with insights arising from modern DNA research, the relative immortality of 'selfish' genes, and some startling recent developments in brain research.
|
1605.07094
|
Sebastian Weichwald
|
Sebastian Weichwald, Tatiana Fomina, Bernhard Sch\"olkopf, Moritz
Grosse-Wentrup
|
A note on the expected minimum error probability in equientropic
channels
| null | null | null | null |
q-bio.NC cs.IT cs.LG math.IT stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
While the channel capacity reflects a theoretical upper bound on the
achievable information transmission rate in the limit of infinitely many bits,
it does not characterise the information transfer of a given encoding routine
with finitely many bits. In this note, we characterise the quality of a code
(i. e. a given encoding routine) by an upper bound on the expected minimum
error probability that can be achieved when using this code. We show that for
equientropic channels this upper bound is minimal for codes with maximal
marginal entropy. As an instructive example we show for the additive white
Gaussian noise (AWGN) channel that random coding---also a capacity achieving
code---indeed maximises the marginal entropy in the limit of infinite messages.
|
[
{
"created": "Mon, 23 May 2016 17:04:57 GMT",
"version": "v1"
},
{
"created": "Tue, 4 Apr 2017 16:55:42 GMT",
"version": "v2"
}
] |
2017-04-05
|
[
[
"Weichwald",
"Sebastian",
""
],
[
"Fomina",
"Tatiana",
""
],
[
"Schölkopf",
"Bernhard",
""
],
[
"Grosse-Wentrup",
"Moritz",
""
]
] |
While the channel capacity reflects a theoretical upper bound on the achievable information transmission rate in the limit of infinitely many bits, it does not characterise the information transfer of a given encoding routine with finitely many bits. In this note, we characterise the quality of a code (i. e. a given encoding routine) by an upper bound on the expected minimum error probability that can be achieved when using this code. We show that for equientropic channels this upper bound is minimal for codes with maximal marginal entropy. As an instructive example we show for the additive white Gaussian noise (AWGN) channel that random coding---also a capacity achieving code---indeed maximises the marginal entropy in the limit of infinite messages.
|
1510.03241
|
Tom Lorimer
|
Florian Gomez, Tom Lorimer, Ruedi Stoop
|
Hopf-type neurons increase input-sensitivity by forming forcing-coupled
ensembles
| null | null | null | null |
q-bio.NC nlin.AO physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Astounding properties of biological sensors can often be mapped onto a
dynamical system in the vicinity a bifurcation. For mammalian hearing, a Hopf
bifurcation description has been shown to work across a whole range of scales,
from individual hair bundles to whole regions of the cochlea. We reveal here
the origin of this scale-invariance, from a general level, applicable to all
neuronal dynamics in the vicinity of a Hopf bifurcation (embracing, e.g.,
Hodgkin-Huxley equations). When coupled by natural 'force-coupling', ensembles
of Hopf oscillators below bifurcation threshold exhibit a collective Hopf
bifurcation. This collective Hopf bifurcation occurs substantially below where
the average of the individual oscillators would bifurcate, with a frequency
profile that is sharpened if compared to the individual oscillators.
|
[
{
"created": "Mon, 12 Oct 2015 11:56:39 GMT",
"version": "v1"
}
] |
2015-10-13
|
[
[
"Gomez",
"Florian",
""
],
[
"Lorimer",
"Tom",
""
],
[
"Stoop",
"Ruedi",
""
]
] |
Astounding properties of biological sensors can often be mapped onto a dynamical system in the vicinity a bifurcation. For mammalian hearing, a Hopf bifurcation description has been shown to work across a whole range of scales, from individual hair bundles to whole regions of the cochlea. We reveal here the origin of this scale-invariance, from a general level, applicable to all neuronal dynamics in the vicinity of a Hopf bifurcation (embracing, e.g., Hodgkin-Huxley equations). When coupled by natural 'force-coupling', ensembles of Hopf oscillators below bifurcation threshold exhibit a collective Hopf bifurcation. This collective Hopf bifurcation occurs substantially below where the average of the individual oscillators would bifurcate, with a frequency profile that is sharpened if compared to the individual oscillators.
|
q-bio/0508035
|
Jonathan Z. Simon
|
Jonathan Z. Simon and Yadong Wang
|
Fully Complex Magnetoencephalography
|
23 pages, 1 table, 5 figures; to appear in Journal of Neuroscience
Methods
| null |
10.1016/j.jneumeth.2005.05.005
| null |
q-bio.NC q-bio.QM
| null |
Complex numbers appear naturally in biology whenever a system can be analyzed
in the frequency domain, such as physiological data from magnetoencephalography
(MEG). For example, the MEG steady state response to a modulated auditory
stimulus generates a complex magnetic field for each MEG channel, equal to the
Fourier transform at the stimulus modulation frequency. The complex nature of
these data sets, often not taken advantage of, is fully exploited here with new
methods. Whole-head, complex magnetic data can be used to estimate complex
neural current sources, and standard methods of source estimation naturally
generalize for complex sources. We show that a general complex neural vector
source is described by its location, magnitude, and direction, but also by a
phase and by an additional perpendicular component. We give natural
interpretations of all the parameters for the complex equivalent-current dipole
by linking them to the underlying neurophysiology. We demonstrate complex
magnetic fields, and their equivalent fully complex current sources, with both
simulations and experimental data.
|
[
{
"created": "Thu, 25 Aug 2005 17:19:29 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Simon",
"Jonathan Z.",
""
],
[
"Wang",
"Yadong",
""
]
] |
Complex numbers appear naturally in biology whenever a system can be analyzed in the frequency domain, such as physiological data from magnetoencephalography (MEG). For example, the MEG steady state response to a modulated auditory stimulus generates a complex magnetic field for each MEG channel, equal to the Fourier transform at the stimulus modulation frequency. The complex nature of these data sets, often not taken advantage of, is fully exploited here with new methods. Whole-head, complex magnetic data can be used to estimate complex neural current sources, and standard methods of source estimation naturally generalize for complex sources. We show that a general complex neural vector source is described by its location, magnitude, and direction, but also by a phase and by an additional perpendicular component. We give natural interpretations of all the parameters for the complex equivalent-current dipole by linking them to the underlying neurophysiology. We demonstrate complex magnetic fields, and their equivalent fully complex current sources, with both simulations and experimental data.
|
1410.2973
|
Peter Jagers
|
Kais Hamza, Peter Jagers, and Fima C. Klebaner
|
On the Establishment, Persistence, and Inevitable Extinction of
Populations
| null | null | null | null |
q-bio.PE math.PR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Comprehensive models of stochastic, clonally reproducing populations are
defined in terms of general branching processes, allowing birth during maternal
life, as for higher organisms, or by splitting, as in cell division. The
populations are assumed to start small, by mutation or immigration, reproduce
supercritically while smaller than the habitat carrying capacity but
subcritically above it. Such populations establish themselves with a
probability wellknown from branching process theory. Once established, they
grow up to a band around the carrying capacity in a time that is logarithmic in
the latter, assumed large. There they prevail during a time period whose
duration is exponential in the carrying capacity. Even populations whose life
style is sustainble in the sense that the habitat carrying capacity is not
eroded but remains the same, ultimately enter an extinction phase, which again
lasts for a time logarithmic in the carrying capacity. However, if the habitat
can carry a population which is large, say millions of individuals, and it
manages to avoid early extinction, time in generations to extinction will be
exorbitantly long, and during it, population composition over ages, types,
lineage etc. will have time to stabilise. This paper aims at an exhaustive
description of the life cycle of such populations, from inception to
extinction, extending and overviewing earlier results. We shall also say some
words on persistence times of populations with smaller carrying capacities and
short life cycles, where the population may indeed be in danger in spite of not
eroding its environment.
|
[
{
"created": "Sat, 11 Oct 2014 08:32:45 GMT",
"version": "v1"
}
] |
2014-10-14
|
[
[
"Hamza",
"Kais",
""
],
[
"Jagers",
"Peter",
""
],
[
"Klebaner",
"Fima C.",
""
]
] |
Comprehensive models of stochastic, clonally reproducing populations are defined in terms of general branching processes, allowing birth during maternal life, as for higher organisms, or by splitting, as in cell division. The populations are assumed to start small, by mutation or immigration, reproduce supercritically while smaller than the habitat carrying capacity but subcritically above it. Such populations establish themselves with a probability wellknown from branching process theory. Once established, they grow up to a band around the carrying capacity in a time that is logarithmic in the latter, assumed large. There they prevail during a time period whose duration is exponential in the carrying capacity. Even populations whose life style is sustainble in the sense that the habitat carrying capacity is not eroded but remains the same, ultimately enter an extinction phase, which again lasts for a time logarithmic in the carrying capacity. However, if the habitat can carry a population which is large, say millions of individuals, and it manages to avoid early extinction, time in generations to extinction will be exorbitantly long, and during it, population composition over ages, types, lineage etc. will have time to stabilise. This paper aims at an exhaustive description of the life cycle of such populations, from inception to extinction, extending and overviewing earlier results. We shall also say some words on persistence times of populations with smaller carrying capacities and short life cycles, where the population may indeed be in danger in spite of not eroding its environment.
|
2007.06468
|
Lucas B\"ottcher
|
Lucas B\"ottcher and Hans Gersbach
|
Incentivizing Narrow-Spectrum Antibiotic Development with Refunding
|
21 pages and 10 figures
|
Bull Math Biol 84, 59 (2022)
|
10.1007/s11538-022-01013-7
| null |
q-bio.PE econ.GN q-fin.EC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The rapid rise of antibiotic resistance is a serious threat to global public
health. Without further incentives, pharmaceutical companies have little
interest in developing antibiotics, since the success probability is low and
development costs are huge. The situation is exacerbated by the "antibiotics
dilemma": Developing narrow-spectrum antibiotics against resistant bacteria is
most beneficial for society, but least attractive for companies since their
usage is more limited than for broad-spectrum drugs and thus sales are low.
Starting from a general mathematical framework for the study of
antibiotic-resistance dynamics with an arbitrary number of antibiotics, we
identify efficient treatment protocols and introduce a market-based refunding
scheme that incentivizes pharmaceutical companies to develop narrow-spectrum
antibiotics: Successful companies can claim a refund from a newly established
antibiotics fund that partially covers their development costs. The proposed
refund involves a fixed and variable part. The latter (i) increases with the
use of the new antibiotic for currently resistant strains in comparison with
other newly developed antibiotics for this purpose---the resistance
premium---and (ii) decreases with the use of this antibiotic for non-resistant
bacteria. We outline how such a refunding scheme can solve the antibiotics
dilemma and cope with various sources of uncertainty inherent in antibiotic
R\&D. Finally, connecting our refunding approach to the recently established
antimicrobial resistance (AMR) action fund, we discuss how the antibiotics fund
can be financed.
|
[
{
"created": "Mon, 13 Jul 2020 16:00:13 GMT",
"version": "v1"
}
] |
2022-06-22
|
[
[
"Böttcher",
"Lucas",
""
],
[
"Gersbach",
"Hans",
""
]
] |
The rapid rise of antibiotic resistance is a serious threat to global public health. Without further incentives, pharmaceutical companies have little interest in developing antibiotics, since the success probability is low and development costs are huge. The situation is exacerbated by the "antibiotics dilemma": Developing narrow-spectrum antibiotics against resistant bacteria is most beneficial for society, but least attractive for companies since their usage is more limited than for broad-spectrum drugs and thus sales are low. Starting from a general mathematical framework for the study of antibiotic-resistance dynamics with an arbitrary number of antibiotics, we identify efficient treatment protocols and introduce a market-based refunding scheme that incentivizes pharmaceutical companies to develop narrow-spectrum antibiotics: Successful companies can claim a refund from a newly established antibiotics fund that partially covers their development costs. The proposed refund involves a fixed and variable part. The latter (i) increases with the use of the new antibiotic for currently resistant strains in comparison with other newly developed antibiotics for this purpose---the resistance premium---and (ii) decreases with the use of this antibiotic for non-resistant bacteria. We outline how such a refunding scheme can solve the antibiotics dilemma and cope with various sources of uncertainty inherent in antibiotic R\&D. Finally, connecting our refunding approach to the recently established antimicrobial resistance (AMR) action fund, we discuss how the antibiotics fund can be financed.
|
1312.4440
|
Vasily Ogryzko V
|
Vasily Ogryzko
|
Comment on Masanari Asano et al. A model of epigenetic evolution based
on theory of open quantum systems. Syst Synth Biol, 2013
|
4 pages
| null | null | null |
q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The comment mostly concerns mis-representation of my position on Quantum
Biology, by stating that I am 'reducing cell's behavior to quantum particles
inside the cell'. I contrast my position with that of McFadden-Al-Khalili, as
well as with the position of Asano et al. I also advertise an idea, described
in our latest paper (Bordonaro, Ogryzko. Quantum Biology at the Cellular level
- elements of the research program, BioSystems, 2013), for the need of
synthetic biology in testing some predictions that follow from our approach.
|
[
{
"created": "Mon, 16 Dec 2013 18:08:07 GMT",
"version": "v1"
}
] |
2013-12-17
|
[
[
"Ogryzko",
"Vasily",
""
]
] |
The comment mostly concerns mis-representation of my position on Quantum Biology, by stating that I am 'reducing cell's behavior to quantum particles inside the cell'. I contrast my position with that of McFadden-Al-Khalili, as well as with the position of Asano et al. I also advertise an idea, described in our latest paper (Bordonaro, Ogryzko. Quantum Biology at the Cellular level - elements of the research program, BioSystems, 2013), for the need of synthetic biology in testing some predictions that follow from our approach.
|
1901.06790
|
Yu-Hui Lin
|
Yu-Hui Lin, Joshua S. Weitz
|
Spatial interactions and oscillatory tragedies of the commons
|
5 pages and 3 figures in main text, 9 pages and 4 figures in
supplementary material
|
Phys. Rev. Lett. 122, 148102 (2019)
|
10.1103/PhysRevLett.122.148102
| null |
q-bio.PE physics.bio-ph
|
http://creativecommons.org/licenses/by/4.0/
|
A tragedy of the commons (TOC) occurs when individuals acting in their own
self-interest deplete commonly-held resources, leading to a worse outcome than
had they cooperated. Over time, the depletion of resources can change
incentives for subsequent actions. Here, we investigate long-term feedback
between game and environment across a continuum of incentives in an
individual-based framework. We identify payoff-dependent transition rules that
lead to oscillatory TOC-s in stochastic simulations and the mean field limit.
Further extending the stochastic model, we find that spatially explicit
interactions can lead to emergent, localized dynamics, including the
propagation of cooperative wave fronts and cluster formation of both social
context and resources. These dynamics suggest new mechanisms underlying how
TOCs arise and how they might be averted.
|
[
{
"created": "Mon, 21 Jan 2019 04:49:02 GMT",
"version": "v1"
}
] |
2019-04-17
|
[
[
"Lin",
"Yu-Hui",
""
],
[
"Weitz",
"Joshua S.",
""
]
] |
A tragedy of the commons (TOC) occurs when individuals acting in their own self-interest deplete commonly-held resources, leading to a worse outcome than had they cooperated. Over time, the depletion of resources can change incentives for subsequent actions. Here, we investigate long-term feedback between game and environment across a continuum of incentives in an individual-based framework. We identify payoff-dependent transition rules that lead to oscillatory TOC-s in stochastic simulations and the mean field limit. Further extending the stochastic model, we find that spatially explicit interactions can lead to emergent, localized dynamics, including the propagation of cooperative wave fronts and cluster formation of both social context and resources. These dynamics suggest new mechanisms underlying how TOCs arise and how they might be averted.
|
2302.09445
|
Siddhartha Srivastava
|
Patrick C. Kinnunen, Siddhartha Srivastava, Zhenlin Wang, Kenneth K.Y.
Ho, Brock A. Humphries, Siyi Chen, Jennifer J. Linderman, Gary D. Luker,
Kathryn E. Luker, Krishna Garikipati
|
Partial differential equation-based inference of migration and
proliferation mechanisms in cancer cell populations
| null | null | null | null |
q-bio.CB
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Targeting signaling pathways that drive cancer cell migration or
proliferation is a common therapeutic approach. A popular experimental
technique, the scratch assay, measures the migration and proliferation-driven
cell monolayer formation. Scratch assay analyses do not differentiate between
migration and proliferation effects and do not attempt to measure dynamic
effects. To improve upon these methods, we combine high-throughput scratch
assays, continuous video microscopy, and variational system identification
(VSI) to infer partial differential equation (PDE) models of cell migration and
proliferation. We capture the evolution of cell density fields over time using
live cell microscopy and automated image processing. We employ VSI techniques
to identify cell density dynamics modeled with first-order kinetics of
advection-diffusion-reaction systems. We present a comparison of our methods to
results obtained using traditional inference approaches on previously analyzed
1-dimensional scratch assay data. We demonstrate the application of this
pipeline on high throughput 2-dimensional scratch assays and find that
decreasing serum levels can decrease random cell migration by approximately
20%. Our integrated experimental and computational pipeline can be adapted for
automatically quantifying the effect of biological perturbations on cell
migration and proliferation in various cell lines.
|
[
{
"created": "Sun, 19 Feb 2023 00:23:46 GMT",
"version": "v1"
}
] |
2023-02-21
|
[
[
"Kinnunen",
"Patrick C.",
""
],
[
"Srivastava",
"Siddhartha",
""
],
[
"Wang",
"Zhenlin",
""
],
[
"Ho",
"Kenneth K. Y.",
""
],
[
"Humphries",
"Brock A.",
""
],
[
"Chen",
"Siyi",
""
],
[
"Linderman",
"Jennifer J.",
""
],
[
"Luker",
"Gary D.",
""
],
[
"Luker",
"Kathryn E.",
""
],
[
"Garikipati",
"Krishna",
""
]
] |
Targeting signaling pathways that drive cancer cell migration or proliferation is a common therapeutic approach. A popular experimental technique, the scratch assay, measures the migration and proliferation-driven cell monolayer formation. Scratch assay analyses do not differentiate between migration and proliferation effects and do not attempt to measure dynamic effects. To improve upon these methods, we combine high-throughput scratch assays, continuous video microscopy, and variational system identification (VSI) to infer partial differential equation (PDE) models of cell migration and proliferation. We capture the evolution of cell density fields over time using live cell microscopy and automated image processing. We employ VSI techniques to identify cell density dynamics modeled with first-order kinetics of advection-diffusion-reaction systems. We present a comparison of our methods to results obtained using traditional inference approaches on previously analyzed 1-dimensional scratch assay data. We demonstrate the application of this pipeline on high throughput 2-dimensional scratch assays and find that decreasing serum levels can decrease random cell migration by approximately 20%. Our integrated experimental and computational pipeline can be adapted for automatically quantifying the effect of biological perturbations on cell migration and proliferation in various cell lines.
|
1711.02994
|
Harish Chandra
|
Rama Bhargava and Harish Chandra
|
Study of bioheat transfer phase change during cryosurgery for an
irregular tumor tissue using EFGM
|
16 pages and 9 figures
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Cryosurgery has been consistently used as an effective treatment to eradicate
irregular tumor tissues. During this process, many difficulties occur such as
intense cooling may also damage the neighboring normal tissues due to the
release of large amount of cold from the cooling probe. In order to protect the
normal tissues in the vicinity of target tumor tissues, coolant was released in
a regulated manner accompanied with the nanoparticle to regulate the size and
orientation of ice balls formed together with improved probe capacity. The
phase change occurs in the target tumor tissues during cryosurgery treatment.
The effective heat capacity method is used for simulation of phase change in
bio-heat transfer equation to take into account the latent heat of phase
transition. The bio-heat transfer equation is solved by using element free
Galerkin method (EFGM) to simulate the phase change problem of biological
tissues subject to nano cryosurgery. In this study, Murshed model with
cylindrical nanoparticles is used for the high thermal conductivity of
nanofluids as compared to Leong Model with the spherical nanoparticle. The
important effects of the interfacial layer at the mushy region (i.e. liquid to
the solid interface), size and concentration of nanoparticles are shown on the
freezing process. This type of problem has applications in biomedical treatment
such as drug delivery. Application of cryosurgery in bio-fluids used for drug
delivery in cancer therapy can be made more efficient in the presence of
nanoparticles (such as Iron oxide ($Fe_{3}O_{4}$), alumina ($Al_{2}O_{3}$) and
gold ($Au$)).
|
[
{
"created": "Mon, 6 Nov 2017 19:38:22 GMT",
"version": "v1"
}
] |
2017-11-09
|
[
[
"Bhargava",
"Rama",
""
],
[
"Chandra",
"Harish",
""
]
] |
Cryosurgery has been consistently used as an effective treatment to eradicate irregular tumor tissues. During this process, many difficulties occur such as intense cooling may also damage the neighboring normal tissues due to the release of large amount of cold from the cooling probe. In order to protect the normal tissues in the vicinity of target tumor tissues, coolant was released in a regulated manner accompanied with the nanoparticle to regulate the size and orientation of ice balls formed together with improved probe capacity. The phase change occurs in the target tumor tissues during cryosurgery treatment. The effective heat capacity method is used for simulation of phase change in bio-heat transfer equation to take into account the latent heat of phase transition. The bio-heat transfer equation is solved by using element free Galerkin method (EFGM) to simulate the phase change problem of biological tissues subject to nano cryosurgery. In this study, Murshed model with cylindrical nanoparticles is used for the high thermal conductivity of nanofluids as compared to Leong Model with the spherical nanoparticle. The important effects of the interfacial layer at the mushy region (i.e. liquid to the solid interface), size and concentration of nanoparticles are shown on the freezing process. This type of problem has applications in biomedical treatment such as drug delivery. Application of cryosurgery in bio-fluids used for drug delivery in cancer therapy can be made more efficient in the presence of nanoparticles (such as Iron oxide ($Fe_{3}O_{4}$), alumina ($Al_{2}O_{3}$) and gold ($Au$)).
|
1905.12100
|
Owen Marschall
|
Owen Marschall, Kyunghyun Cho, Cristina Savin
|
Using local plasticity rules to train recurrent neural networks
|
Abstract submission to Computational and Systems Neuroscience
(Cosyne) 2019, accepted
| null | null | null |
q-bio.NC cs.AI
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
To learn useful dynamics on long time scales, neurons must use plasticity
rules that account for long-term, circuit-wide effects of synaptic changes. In
other words, neural circuits must solve a credit assignment problem to
appropriately assign responsibility for global network behavior to individual
circuit components. Furthermore, biological constraints demand that plasticity
rules are spatially and temporally local; that is, synaptic changes can depend
only on variables accessible to the pre- and postsynaptic neurons. While
artificial intelligence offers a computational solution for credit assignment,
namely backpropagation through time (BPTT), this solution is wildly
biologically implausible. It requires both nonlocal computations and unlimited
memory capacity, as any synaptic change is a complicated function of the entire
history of network activity. Similar nonlocality issues plague other approaches
such as FORCE (Sussillo et al. 2009). Overall, we are still missing a model for
learning in recurrent circuits that both works computationally and uses only
local updates. Leveraging recent advances in machine learning on approximating
gradients for BPTT, we derive biologically plausible plasticity rules that
enable recurrent networks to accurately learn long-term dependencies in
sequential data. The solution takes the form of neurons with segregated voltage
compartments, with several synaptic sub-populations that have different
functional properties. The network operates in distinct phases during which
each synaptic sub-population is updated by its own local plasticity rule. Our
results provide new insights into the potential roles of segregated dendritic
compartments, branch-specific inhibition, and global circuit phases in
learning.
|
[
{
"created": "Tue, 28 May 2019 21:32:26 GMT",
"version": "v1"
}
] |
2019-05-30
|
[
[
"Marschall",
"Owen",
""
],
[
"Cho",
"Kyunghyun",
""
],
[
"Savin",
"Cristina",
""
]
] |
To learn useful dynamics on long time scales, neurons must use plasticity rules that account for long-term, circuit-wide effects of synaptic changes. In other words, neural circuits must solve a credit assignment problem to appropriately assign responsibility for global network behavior to individual circuit components. Furthermore, biological constraints demand that plasticity rules are spatially and temporally local; that is, synaptic changes can depend only on variables accessible to the pre- and postsynaptic neurons. While artificial intelligence offers a computational solution for credit assignment, namely backpropagation through time (BPTT), this solution is wildly biologically implausible. It requires both nonlocal computations and unlimited memory capacity, as any synaptic change is a complicated function of the entire history of network activity. Similar nonlocality issues plague other approaches such as FORCE (Sussillo et al. 2009). Overall, we are still missing a model for learning in recurrent circuits that both works computationally and uses only local updates. Leveraging recent advances in machine learning on approximating gradients for BPTT, we derive biologically plausible plasticity rules that enable recurrent networks to accurately learn long-term dependencies in sequential data. The solution takes the form of neurons with segregated voltage compartments, with several synaptic sub-populations that have different functional properties. The network operates in distinct phases during which each synaptic sub-population is updated by its own local plasticity rule. Our results provide new insights into the potential roles of segregated dendritic compartments, branch-specific inhibition, and global circuit phases in learning.
|
1706.02187
|
Victor Manuel Trejos Montoya
|
Ang\'elica M. Alzate Iba\~nez, Carlos Ocampo-Martinez, Carlos A.
Cardona Alzate, V\'ictor M. Trejos M
|
Monitoring management criterion of an anaerobic digester using an
explicit model based on temperature and pH
|
20 pages, 9 figures, full paper
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, the stability analysis of an anaerobic digestion process is
presented. The analysis is performed using a simplified mathematical model,
which includes explicit temperature and pH dependence on kinetic growth rates.
A detailed nonlinear and bifurcation analyses are performed in order to study
the effects of temperature and pH parameters on the process behaviour. In
addition, both safety and optimal operation regions of the bioreactor are
established. Based on bifurcation diagrams, it is observed that the washout
condition occurs by combining a fold bifurcation and a transcritical
bifurcation. Consequently, to prevent the washout and guarantee optimal
operation conditions of the bioreactor, a risk criterion oriented to monitor
the bioprocess on-line is proposed, allowing to detect the system
destabilisation.
|
[
{
"created": "Tue, 6 Jun 2017 15:44:06 GMT",
"version": "v1"
}
] |
2017-06-08
|
[
[
"Ibañez",
"Angélica M. Alzate",
""
],
[
"Ocampo-Martinez",
"Carlos",
""
],
[
"Alzate",
"Carlos A. Cardona",
""
],
[
"M",
"Víctor M. Trejos",
""
]
] |
In this paper, the stability analysis of an anaerobic digestion process is presented. The analysis is performed using a simplified mathematical model, which includes explicit temperature and pH dependence on kinetic growth rates. A detailed nonlinear and bifurcation analyses are performed in order to study the effects of temperature and pH parameters on the process behaviour. In addition, both safety and optimal operation regions of the bioreactor are established. Based on bifurcation diagrams, it is observed that the washout condition occurs by combining a fold bifurcation and a transcritical bifurcation. Consequently, to prevent the washout and guarantee optimal operation conditions of the bioreactor, a risk criterion oriented to monitor the bioprocess on-line is proposed, allowing to detect the system destabilisation.
|
2401.06823
|
Pengyi Yang
|
Manoj M Wagle, Siqu Long, Carissa Chen, Chunlei Liu, Pengyi Yang
|
Interpretable deep learning in single-cell omics
| null | null | null | null |
q-bio.GN cs.LG
|
http://creativecommons.org/licenses/by/4.0/
|
Recent developments in single-cell omics technologies have enabled the
quantification of molecular profiles in individual cells at an unparalleled
resolution. Deep learning, a rapidly evolving sub-field of machine learning,
has instilled a significant interest in single-cell omics research due to its
remarkable success in analysing heterogeneous high-dimensional single-cell
omics data. Nevertheless, the inherent multi-layer nonlinear architecture of
deep learning models often makes them `black boxes' as the reasoning behind
predictions is often unknown and not transparent to the user. This has
stimulated an increasing body of research for addressing the lack of
interpretability in deep learning models, especially in single-cell omics data
analyses, where the identification and understanding of molecular regulators
are crucial for interpreting model predictions and directing downstream
experimental validations. In this work, we introduce the basics of single-cell
omics technologies and the concept of interpretable deep learning. This is
followed by a review of the recent interpretable deep learning models applied
to various single-cell omics research. Lastly, we highlight the current
limitations and discuss potential future directions. We anticipate this review
to bring together the single-cell and machine learning research communities to
foster future development and application of interpretable deep learning in
single-cell omics research.
|
[
{
"created": "Thu, 11 Jan 2024 23:59:37 GMT",
"version": "v1"
}
] |
2024-01-17
|
[
[
"Wagle",
"Manoj M",
""
],
[
"Long",
"Siqu",
""
],
[
"Chen",
"Carissa",
""
],
[
"Liu",
"Chunlei",
""
],
[
"Yang",
"Pengyi",
""
]
] |
Recent developments in single-cell omics technologies have enabled the quantification of molecular profiles in individual cells at an unparalleled resolution. Deep learning, a rapidly evolving sub-field of machine learning, has instilled a significant interest in single-cell omics research due to its remarkable success in analysing heterogeneous high-dimensional single-cell omics data. Nevertheless, the inherent multi-layer nonlinear architecture of deep learning models often makes them `black boxes' as the reasoning behind predictions is often unknown and not transparent to the user. This has stimulated an increasing body of research for addressing the lack of interpretability in deep learning models, especially in single-cell omics data analyses, where the identification and understanding of molecular regulators are crucial for interpreting model predictions and directing downstream experimental validations. In this work, we introduce the basics of single-cell omics technologies and the concept of interpretable deep learning. This is followed by a review of the recent interpretable deep learning models applied to various single-cell omics research. Lastly, we highlight the current limitations and discuss potential future directions. We anticipate this review to bring together the single-cell and machine learning research communities to foster future development and application of interpretable deep learning in single-cell omics research.
|
1704.01379
|
Valentine Svensson
|
Valentine Svensson, Roser Vento-Tormo, Sarah A Teichmann
|
Exponential scaling of single-cell RNA-seq in the last decade
|
13 pages, 1 figure. Manuscript restructured for readability, with
improved language
| null | null | null |
q-bio.GN
|
http://creativecommons.org/licenses/by/4.0/
|
The ability to measure the transcriptomes of single cells has only been
feasible for a few years, and is becoming an extremely popular assay. While
many types of analysis and questions can be answered using single cell
RNA-sequencing, a central focus is the ability to survey the diversity of cell
types within a sample. Unbiased and reproducible cataloging of distinct cell
types requires large numbers of cells. Technological developments and protocol
improvements have fuelled a consistent exponential increase in the numbers of
cells studied in single cell RNA-seq analyses. In this perspective, we will
highlight the key technological developments which have enabled this growth in
data.
|
[
{
"created": "Wed, 5 Apr 2017 12:18:29 GMT",
"version": "v1"
},
{
"created": "Tue, 8 Aug 2017 16:54:08 GMT",
"version": "v2"
}
] |
2017-08-09
|
[
[
"Svensson",
"Valentine",
""
],
[
"Vento-Tormo",
"Roser",
""
],
[
"Teichmann",
"Sarah A",
""
]
] |
The ability to measure the transcriptomes of single cells has only been feasible for a few years, and is becoming an extremely popular assay. While many types of analysis and questions can be answered using single cell RNA-sequencing, a central focus is the ability to survey the diversity of cell types within a sample. Unbiased and reproducible cataloging of distinct cell types requires large numbers of cells. Technological developments and protocol improvements have fuelled a consistent exponential increase in the numbers of cells studied in single cell RNA-seq analyses. In this perspective, we will highlight the key technological developments which have enabled this growth in data.
|
1008.5390
|
Hesam Dashti
|
Hesam T. Dashti, Jernej Tonejc, Adel Ardalan, Alireza F. Siahpirani,
Sabrina Guettes, Zohreh Sharif, Liya Wang, Amir H. Assadi
|
Applications of Machine Learning Methods to Quantifying Phenotypic
Traits that Distinguish the Wild Type from the Mutant Arabidopsis Thaliana
Seedlings during Root Gravitropism
|
International Conference on Bioinformatics and Computational Biology,
WorldComp 2010
| null | null | null |
q-bio.QM cs.CE cs.LG q-bio.GN
|
http://creativecommons.org/licenses/by-nc-sa/3.0/
|
Post-genomic research deals with challenging problems in screening genomes of
organisms for particular functions or potential for being the targets of
genetic engineering for desirable biological features. 'Phenotyping' of wild
type and mutants is a time-consuming and costly effort by many individuals.
This article is a preliminary progress report in research on large-scale
automation of phenotyping steps (imaging, informatics and data analysis) needed
to study plant gene-proteins networks that influence growth and development of
plants. Our results undermine the significance of phenotypic traits that are
implicit in patterns of dynamics in plant root response to sudden changes of
its environmental conditions, such as sudden re-orientation of the root tip
against the gravity vector. Including dynamic features besides the common
morphological ones has paid off in design of robust and accurate machine
learning methods to automate a typical phenotyping scenario, i.e. to
distinguish the wild type from the mutants.
|
[
{
"created": "Tue, 31 Aug 2010 18:54:33 GMT",
"version": "v1"
}
] |
2010-09-06
|
[
[
"Dashti",
"Hesam T.",
""
],
[
"Tonejc",
"Jernej",
""
],
[
"Ardalan",
"Adel",
""
],
[
"Siahpirani",
"Alireza F.",
""
],
[
"Guettes",
"Sabrina",
""
],
[
"Sharif",
"Zohreh",
""
],
[
"Wang",
"Liya",
""
],
[
"Assadi",
"Amir H.",
""
]
] |
Post-genomic research deals with challenging problems in screening genomes of organisms for particular functions or potential for being the targets of genetic engineering for desirable biological features. 'Phenotyping' of wild type and mutants is a time-consuming and costly effort by many individuals. This article is a preliminary progress report in research on large-scale automation of phenotyping steps (imaging, informatics and data analysis) needed to study plant gene-proteins networks that influence growth and development of plants. Our results undermine the significance of phenotypic traits that are implicit in patterns of dynamics in plant root response to sudden changes of its environmental conditions, such as sudden re-orientation of the root tip against the gravity vector. Including dynamic features besides the common morphological ones has paid off in design of robust and accurate machine learning methods to automate a typical phenotyping scenario, i.e. to distinguish the wild type from the mutants.
|
1009.0857
|
Chris Wiggins PhD
|
Jonathan E. Bronson, Jake M. Hofman, Jingyi Fei, Ruben L. Gonzalez
Jr., Chris H. Wiggins
|
Graphical models for inferring single molecule dynamics
|
22 pages, 5 figures; Journal special issue for workshop papers from
"New Problems and Methods in Computational Biology" A workshop at the
Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS
2009) Whistler, BC, Canada, December 11 or 12, 2009. (cf.
http://videolectures.net/nipsworkshops09_computational_biology/)
| null | null | null |
q-bio.QM physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Background: The recent explosion of experimental techniques in single
molecule biophysics has generated a variety of novel time series data requiring
equally novel computational tools for analysis and inference. This article
describes in general terms how graphical modeling may be used to learn from
biophysical time series data using the variational Bayesian expectation
maximization algorithm (VBEM). The discussion is illustrated by the example of
single-molecule fluorescence resonance energy transfer (smFRET) versus time
data, where the smFRET time series is modeled as a hidden Markov model (HMM)
with Gaussian observables. A detailed description of smFRET is provided as
well. Results: The VBEM algorithm returns the model's evidence and an
approximating posterior parameter distribution given the data. The former
provides a metric for model selection via maximum evidence (ME), and the latter
a description of the model's parameters learned from the data. ME/VBEM provide
several advantages over the more commonly used approach of maximum likelihood
(ML) optimized by the expectation maximization (EM) algorithm, the most
important being a natural form of model selection and a well-posed
(non-divergent) optimization problem. Conclusions: The results demonstrate the
utility of graphical modeling for inference of dynamic processes in single
molecule biophysics.
|
[
{
"created": "Sat, 4 Sep 2010 18:15:19 GMT",
"version": "v1"
}
] |
2010-09-07
|
[
[
"Bronson",
"Jonathan E.",
""
],
[
"Hofman",
"Jake M.",
""
],
[
"Fei",
"Jingyi",
""
],
[
"Gonzalez",
"Ruben L.",
"Jr."
],
[
"Wiggins",
"Chris H.",
""
]
] |
Background: The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM). The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET) versus time data, where the smFRET time series is modeled as a hidden Markov model (HMM) with Gaussian observables. A detailed description of smFRET is provided as well. Results: The VBEM algorithm returns the model's evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME), and the latter a description of the model's parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML) optimized by the expectation maximization (EM) algorithm, the most important being a natural form of model selection and a well-posed (non-divergent) optimization problem. Conclusions: The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics.
|
q-bio/0505052
|
Antonio Trovato
|
Jayanth R. Banavar, Marek Cieplak, Alessandro Flammini, Trinh X.
Hoang, Randall D. Kamien, Timothy Lezon, Davide Marenduzzo, Amos Maritan,
Flavio Seno, Yehuda Snir, Antonio Trovato
|
Geometry of proteins: hydrogen bonding, sterics and marginally compact
tubes
|
12 pages, no figures, revised version accepted for publication in
Phisycal Review E
| null |
10.1103/PhysRevE.73.031921
| null |
q-bio.BM
| null |
The functionality of proteins is related to their structure in the native
state. Protein structures are made up of emergent building blocks of helices
and almost planar sheets. A simple coarse-grained geometrical model of a
flexible tube barely subject to compaction provides a unified framework for
understanding the common character of globular proteins.We argue that a recent
critique of the tube idea is not well founded.
|
[
{
"created": "Fri, 27 May 2005 10:30:38 GMT",
"version": "v1"
},
{
"created": "Mon, 20 Mar 2006 11:39:44 GMT",
"version": "v2"
}
] |
2009-11-11
|
[
[
"Banavar",
"Jayanth R.",
""
],
[
"Cieplak",
"Marek",
""
],
[
"Flammini",
"Alessandro",
""
],
[
"Hoang",
"Trinh X.",
""
],
[
"Kamien",
"Randall D.",
""
],
[
"Lezon",
"Timothy",
""
],
[
"Marenduzzo",
"Davide",
""
],
[
"Maritan",
"Amos",
""
],
[
"Seno",
"Flavio",
""
],
[
"Snir",
"Yehuda",
""
],
[
"Trovato",
"Antonio",
""
]
] |
The functionality of proteins is related to their structure in the native state. Protein structures are made up of emergent building blocks of helices and almost planar sheets. A simple coarse-grained geometrical model of a flexible tube barely subject to compaction provides a unified framework for understanding the common character of globular proteins.We argue that a recent critique of the tube idea is not well founded.
|
1803.08541
|
Andrea Avena-Koenigsberger
|
Andrea Avena-Koenigsberger, Xiaoran Yan, Artemy Kolchinsky, Martijn
van den Heuvel, Patric Hagmann and Olaf Sporns
|
A spectrum of routing strategies for brain networks
| null | null |
10.1371/journal.pcbi.1006833
| null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Communication of signals among nodes in a complex network poses fundamental
problems of efficiency and cost. Routing of messages along shortest paths
requires global information about the topology, while spreading by diffusion,
which operates according to local topological features, is informationally
"cheap" but inefficient. We introduce a stochastic model for network
communication that combines varying amounts of local and global information
about the network topology. The model generates a continuous spectrum of
dynamics that converge onto shortest-path and random-walk (diffusion)
communication processes at the limiting extremes. We implement the model on two
cohorts of human connectome networks and investigate the effects of varying
amounts of local and global information on the network's communication cost. We
identify routing strategies that approach a (highly efficient) shortest-path
communication process with a relatively small amount of global information.
Moreover, we show that the cost of routing messages from and to hub nodes
varies as a function of the amount of global information driving the system's
dynamics. Finally, we implement the model to identify individual subject
differences from a communication dynamics point of view. The present framework
departs from the classical shortest paths vs. diffusion dichotomy, suggesting
instead that brain networks may exhibit different types of communication
dynamics depending on varying functional demands and the availability of
resources.
|
[
{
"created": "Thu, 22 Mar 2018 18:46:21 GMT",
"version": "v1"
}
] |
2019-06-19
|
[
[
"Avena-Koenigsberger",
"Andrea",
""
],
[
"Yan",
"Xiaoran",
""
],
[
"Kolchinsky",
"Artemy",
""
],
[
"Heuvel",
"Martijn van den",
""
],
[
"Hagmann",
"Patric",
""
],
[
"Sporns",
"Olaf",
""
]
] |
Communication of signals among nodes in a complex network poses fundamental problems of efficiency and cost. Routing of messages along shortest paths requires global information about the topology, while spreading by diffusion, which operates according to local topological features, is informationally "cheap" but inefficient. We introduce a stochastic model for network communication that combines varying amounts of local and global information about the network topology. The model generates a continuous spectrum of dynamics that converge onto shortest-path and random-walk (diffusion) communication processes at the limiting extremes. We implement the model on two cohorts of human connectome networks and investigate the effects of varying amounts of local and global information on the network's communication cost. We identify routing strategies that approach a (highly efficient) shortest-path communication process with a relatively small amount of global information. Moreover, we show that the cost of routing messages from and to hub nodes varies as a function of the amount of global information driving the system's dynamics. Finally, we implement the model to identify individual subject differences from a communication dynamics point of view. The present framework departs from the classical shortest paths vs. diffusion dichotomy, suggesting instead that brain networks may exhibit different types of communication dynamics depending on varying functional demands and the availability of resources.
|
0710.4030
|
Benjamin Audit
|
Edward-Benedict Brodie (of Brodie) (Phys-ENS), Samuel Nicolay
(Phys-ENS), Marie Touchon (CGM), Benjamin Audit (Phys-ENS), Yves
D'Aubenton-Carafa (CGM), Claude Thermes (CGM), Alain Arneodo (Phys-ENS)
|
From DNA sequence analysis to modeling replication in the human genome
| null |
Physical Review Letters 94, 24 (2005) 248103
| null | null |
q-bio.GN
| null |
We explore the large-scale behavior of nucleotide compositional strand
asymmetries along human chromosomes. As we observe for 7 of 9 origins of
replication experimentally identified so far, the (TA+GC) skew displays rather
sharp upward jumps, with a linear decreasing profile in between two successive
jumps. We present a model of replication with well positioned replication
origins and random terminations that accounts for the observed characteristic
serrated skew profiles. We succeed in identifying 287 pairs of putative
adjacent replication origins with an origin spacing approximately 1-2 Mbp that
are likely to correspond to replication foci observed in interphase nuclei and
recognized as stable structures that persist throughout subsequent cell
generations.
|
[
{
"created": "Mon, 22 Oct 2007 12:01:37 GMT",
"version": "v1"
}
] |
2007-10-23
|
[
[
"Brodie",
"Edward-Benedict",
"",
"of Brodie"
],
[
"Nicolay",
"Samuel",
"",
"Phys-ENS"
],
[
"Touchon",
"Marie",
"",
"CGM"
],
[
"Audit",
"Benjamin",
"",
"Phys-ENS"
],
[
"D'Aubenton-Carafa",
"Yves",
"",
"CGM"
],
[
"Thermes",
"Claude",
"",
"CGM"
],
[
"Arneodo",
"Alain",
"",
"Phys-ENS"
]
] |
We explore the large-scale behavior of nucleotide compositional strand asymmetries along human chromosomes. As we observe for 7 of 9 origins of replication experimentally identified so far, the (TA+GC) skew displays rather sharp upward jumps, with a linear decreasing profile in between two successive jumps. We present a model of replication with well positioned replication origins and random terminations that accounts for the observed characteristic serrated skew profiles. We succeed in identifying 287 pairs of putative adjacent replication origins with an origin spacing approximately 1-2 Mbp that are likely to correspond to replication foci observed in interphase nuclei and recognized as stable structures that persist throughout subsequent cell generations.
|
1501.05006
|
Sarthok Sircar
|
S. Sircar and J.N. Majumdar
|
Chapter 9 TISSUE ENGINEERING
|
Book chapter: 17 pages, 18 figures
| null | null | null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Tissue Engineering (TE) is an interdisciplinary field dealing with the
principles of engineering and life sciences toward the development of
biological substitutes that restore, maintain, or improve tissue function or a
whole organ. Currently, TE is emerging as an invaluable field of study and is
one of the most promising fields for the next century. The ultimate goal is to
develop powerful new therapies for biological substitutes - that will
successfully restore the structural and functional disorders of human and
animal system.
|
[
{
"created": "Tue, 20 Jan 2015 22:33:41 GMT",
"version": "v1"
}
] |
2015-01-22
|
[
[
"Sircar",
"S.",
""
],
[
"Majumdar",
"J. N.",
""
]
] |
Tissue Engineering (TE) is an interdisciplinary field dealing with the principles of engineering and life sciences toward the development of biological substitutes that restore, maintain, or improve tissue function or a whole organ. Currently, TE is emerging as an invaluable field of study and is one of the most promising fields for the next century. The ultimate goal is to develop powerful new therapies for biological substitutes - that will successfully restore the structural and functional disorders of human and animal system.
|
q-bio/0403002
|
Steven N. Evans
|
David Steinsaltz, Steven N. Evans, Kenneth W. Wachter
|
A generalized model of mutation-selection balance with applications to
aging
|
20 pages Updated to include more historical comment and references to
the literature, as well as to make clear how our non-linear, non-Markovian
model differs from previous linear, Markovian particle system and
measure-valued diffusion models. Further updated to take into account
referee's comments
| null | null | null |
q-bio.PE math.PR
| null |
A probability model is presented for the dynamics of mutation-selection
balance in a haploid infinite-population infinite-sites setting sufficiently
general to cover mutation-driven changes in full age-specific demographic
schedules. The model accommodates epistatic as well as additive selective
costs. Closed form characterizations are obtained for solutions in finite time,
along with proofs of convergence to stationary distributions and a proof of the
uniqueness of solutions in a restricted case. Examples are given of
applications to the biodemography of aging, including instabilities in current
formulations of mutation accumulation.
|
[
{
"created": "Mon, 1 Mar 2004 17:24:39 GMT",
"version": "v1"
},
{
"created": "Wed, 2 Jun 2004 18:35:44 GMT",
"version": "v2"
},
{
"created": "Thu, 7 Oct 2004 03:53:48 GMT",
"version": "v3"
}
] |
2007-05-23
|
[
[
"Steinsaltz",
"David",
""
],
[
"Evans",
"Steven N.",
""
],
[
"Wachter",
"Kenneth W.",
""
]
] |
A probability model is presented for the dynamics of mutation-selection balance in a haploid infinite-population infinite-sites setting sufficiently general to cover mutation-driven changes in full age-specific demographic schedules. The model accommodates epistatic as well as additive selective costs. Closed form characterizations are obtained for solutions in finite time, along with proofs of convergence to stationary distributions and a proof of the uniqueness of solutions in a restricted case. Examples are given of applications to the biodemography of aging, including instabilities in current formulations of mutation accumulation.
|
q-bio/0701008
|
Arne Traulsen
|
Jorge M. Pacheco, Arne Traulsen, Martin A. Nowak
|
Co-evolution of strategy and structure in complex networks with
dynamical linking
| null |
Physical Review Letters 97, 025103 (2006)
|
10.1103/PhysRevLett.97.258103
| null |
q-bio.PE
| null |
Here we introduce a model in which individuals differ in the rate at which
they seek new interactions with others, making rational decisions modeled as
general symmetric two-player games. Once a link between two individuals has
formed, the productivity of this link is evaluated. Links can be broken off at
different rates. We provide analytic results for the limiting cases where
linking dynamics is much faster than evolutionary dynamics and vice-versa, and
show how the individual capacity of forming new links or severing inconvenient
ones maps into the problem of strategy evolution in a well-mixed population
under a different game. For intermediate ranges, we investigate numerically the
detailed interplay determined by these two time-scales and show that the scope
of validity of the analytical results extends to a much wider ratio of time
scales than expected.
|
[
{
"created": "Wed, 3 Jan 2007 23:07:49 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Pacheco",
"Jorge M.",
""
],
[
"Traulsen",
"Arne",
""
],
[
"Nowak",
"Martin A.",
""
]
] |
Here we introduce a model in which individuals differ in the rate at which they seek new interactions with others, making rational decisions modeled as general symmetric two-player games. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. We provide analytic results for the limiting cases where linking dynamics is much faster than evolutionary dynamics and vice-versa, and show how the individual capacity of forming new links or severing inconvenient ones maps into the problem of strategy evolution in a well-mixed population under a different game. For intermediate ranges, we investigate numerically the detailed interplay determined by these two time-scales and show that the scope of validity of the analytical results extends to a much wider ratio of time scales than expected.
|
1208.0537
|
Tom Michoel
|
Jianlong Qi, Tom Michoel
|
Context-specific transcriptional regulatory network inference from
global gene expression maps using double two-way t-tests
|
8 pages, 9 figures, 2 tables; software available at
http://twixtrix.googlecode.com
| null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Transcriptional regulatory network inference methods have been studied for
years. Most of them relie on complex mathematical and algorithmic concepts,
making them hard to adapt, re-implement or integrate with other methods. To
address this problem, we introduce a novel method based on a minimal
statistical model for observing transcriptional regulatory interactions in
noisy expression data, which assumes that transcription factors (TFs) and their
targets are both differentially expressed in a gene-specific, critical sample
contrast, as measured by repeated two-way t-tests. This method is conceptually
simple and easy to implement and integrate in any statistical software
environment. Benchmarking on standard E. coli and yeast reference datasets
showed that it performs equally well as the best existing methods. Analysis of
the predicted interactions suggested that it works best to infer
context-specific TF-target interactions which only co-express locally. We
confirmed this hypothesis on a dataset of more than 1,000 normal human tissue
samples, where we found that our method predicts highly tissue-specific and
functionally relevant interactions, whereas a global co-expression method only
associates general TFs to non-specific biological processes.
|
[
{
"created": "Thu, 2 Aug 2012 16:41:29 GMT",
"version": "v1"
}
] |
2012-08-03
|
[
[
"Qi",
"Jianlong",
""
],
[
"Michoel",
"Tom",
""
]
] |
Transcriptional regulatory network inference methods have been studied for years. Most of them relie on complex mathematical and algorithmic concepts, making them hard to adapt, re-implement or integrate with other methods. To address this problem, we introduce a novel method based on a minimal statistical model for observing transcriptional regulatory interactions in noisy expression data, which assumes that transcription factors (TFs) and their targets are both differentially expressed in a gene-specific, critical sample contrast, as measured by repeated two-way t-tests. This method is conceptually simple and easy to implement and integrate in any statistical software environment. Benchmarking on standard E. coli and yeast reference datasets showed that it performs equally well as the best existing methods. Analysis of the predicted interactions suggested that it works best to infer context-specific TF-target interactions which only co-express locally. We confirmed this hypothesis on a dataset of more than 1,000 normal human tissue samples, where we found that our method predicts highly tissue-specific and functionally relevant interactions, whereas a global co-expression method only associates general TFs to non-specific biological processes.
|
2207.06630
|
Fikret Aydin
|
Fikret Aydin (1), Konstantia Georgouli (1), Gautham Dharuman (1),
James N. Glosli (1), Felice C. Lightstone (1), Helgi I. Ing\'olfsson (1),
Peer-Timo Bremer (2), Harsh Bhatia (2) ((1) Physical & Life Sciences,
Lawrence Livermore National Laboratory, (2) Center for Applied Scientific
Computing, Lawrence Livermore National Laboratory)
|
Identifying Orientation-specific Lipid-protein Fingerprints using Deep
Learning
| null | null | null | null |
q-bio.BM cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Improved understanding of the relation between the behavior of RAS and RAF
proteins and the local lipid environment in the cell membrane is critical for
getting insights into the mechanisms underlying cancer formation. In this work,
we employ deep learning (DL) to learn this relationship by predicting protein
orientational states of RAS and RAS-RAF protein complexes with respect to the
lipid membrane based on the lipid densities around the protein domains from
coarse-grained (CG) molecular dynamics (MD) simulations. Our DL model can
predict six protein states with an overall accuracy of over 80%. The findings
of this work offer new insights into how the proteins modulate the lipid
environment, which in turn may assist designing novel therapies to regulate
such interactions in the mechanisms associated with cancer development.
|
[
{
"created": "Thu, 14 Jul 2022 03:01:49 GMT",
"version": "v1"
}
] |
2022-07-15
|
[
[
"Aydin",
"Fikret",
""
],
[
"Georgouli",
"Konstantia",
""
],
[
"Dharuman",
"Gautham",
""
],
[
"Glosli",
"James N.",
""
],
[
"Lightstone",
"Felice C.",
""
],
[
"Ingólfsson",
"Helgi I.",
""
],
[
"Bremer",
"Peer-Timo",
""
],
[
"Bhatia",
"Harsh",
""
]
] |
Improved understanding of the relation between the behavior of RAS and RAF proteins and the local lipid environment in the cell membrane is critical for getting insights into the mechanisms underlying cancer formation. In this work, we employ deep learning (DL) to learn this relationship by predicting protein orientational states of RAS and RAS-RAF protein complexes with respect to the lipid membrane based on the lipid densities around the protein domains from coarse-grained (CG) molecular dynamics (MD) simulations. Our DL model can predict six protein states with an overall accuracy of over 80%. The findings of this work offer new insights into how the proteins modulate the lipid environment, which in turn may assist designing novel therapies to regulate such interactions in the mechanisms associated with cancer development.
|
1010.0339
|
Jin Yang
|
Qiang Chang and Jin Yang
|
Monte Carlo Algorithm for Simulating Reversible Aggregation of Multisite
Particles
|
8 pages, 3 figures
|
Physical Review E, 83, 056701, 2011
|
10.1103/PhysRevE.83.056701
| null |
q-bio.QM physics.comp-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We present an efficient and exact Monte Carlo algorithm to simulate
reversible aggregation of particles with dedicated binding sites. This method
introduces a novel data structure of dynamic bond tree to record clusters and
sequences of bond formations. The algorithm achieves a constant time cost for
processing cluster association and a cost between $\mathcal{O}(\log M)$ and
$\mathcal{O}(M)$ for processing bond dissociation in clusters with $M$ bonds.
The algorithm is statistically exact and can reproduce results obtained by the
standard method. We applied the method to simulate a trivalent ligand and a
bivalent receptor clustering system and obtained an average scaling of
$\mathcal{O}(M^{0.45})$ for processing bond dissociation in acyclic
aggregation, compared to a linear scaling with the cluster size in standard
methods. The algorithm also demands substantially less memory than the
conventional method.
|
[
{
"created": "Sat, 2 Oct 2010 14:29:06 GMT",
"version": "v1"
},
{
"created": "Mon, 26 Sep 2011 06:03:54 GMT",
"version": "v2"
}
] |
2011-09-27
|
[
[
"Chang",
"Qiang",
""
],
[
"Yang",
"Jin",
""
]
] |
We present an efficient and exact Monte Carlo algorithm to simulate reversible aggregation of particles with dedicated binding sites. This method introduces a novel data structure of dynamic bond tree to record clusters and sequences of bond formations. The algorithm achieves a constant time cost for processing cluster association and a cost between $\mathcal{O}(\log M)$ and $\mathcal{O}(M)$ for processing bond dissociation in clusters with $M$ bonds. The algorithm is statistically exact and can reproduce results obtained by the standard method. We applied the method to simulate a trivalent ligand and a bivalent receptor clustering system and obtained an average scaling of $\mathcal{O}(M^{0.45})$ for processing bond dissociation in acyclic aggregation, compared to a linear scaling with the cluster size in standard methods. The algorithm also demands substantially less memory than the conventional method.
|
2005.11767
|
Suban Sahoo
|
Seshu Vardhan, Bharat Z. Dholakiya and Suban K Sahoo
|
Protein-ligand interaction study to identify potential dietary compounds
binding at the active site of therapeutic target proteins of SARS-CoV-2
| null | null | null | null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Objective: Total 186 biologically important phenylpropanoids and polyketides
compounds from different Indian medicinal plants and dietary sources were
screened to filter potential compounds that bind at the active site of the
therapeutic target proteins of SARS-CoV-2. Method: The molecular docking
studies were carried out by using the Autodock Vina. The in silico ADMET and
drug-likeness properties of the compounds were predicted from SwissADME server.
Result: The molecular docking study of the 186 compounds with the therapeutic
target proteins (Mpro, PLpro, RdRp, SGp and ACE2) of SARS-CoV-2 resulted 40
compounds that bind at the active site with dock score above -8.0 kcal/mol.
Conclusion: Based on the in silico ADMET study and drug-likeness prediction of
40 compounds, we proposed petunidin, baicalein, cyanidin,
7-hydroxy-3',4'-methylenedioxyflavan, quercetin and ellagic acid among the 186
biologically important phenylpropanoids and polyketides as potential lead
compounds, which can further be investigated pharmacologically and clinically
to formulate therapeutic approaches for the COVID-19.
|
[
{
"created": "Sun, 24 May 2020 15:04:52 GMT",
"version": "v1"
}
] |
2020-05-26
|
[
[
"Vardhan",
"Seshu",
""
],
[
"Dholakiya",
"Bharat Z.",
""
],
[
"Sahoo",
"Suban K",
""
]
] |
Objective: Total 186 biologically important phenylpropanoids and polyketides compounds from different Indian medicinal plants and dietary sources were screened to filter potential compounds that bind at the active site of the therapeutic target proteins of SARS-CoV-2. Method: The molecular docking studies were carried out by using the Autodock Vina. The in silico ADMET and drug-likeness properties of the compounds were predicted from SwissADME server. Result: The molecular docking study of the 186 compounds with the therapeutic target proteins (Mpro, PLpro, RdRp, SGp and ACE2) of SARS-CoV-2 resulted 40 compounds that bind at the active site with dock score above -8.0 kcal/mol. Conclusion: Based on the in silico ADMET study and drug-likeness prediction of 40 compounds, we proposed petunidin, baicalein, cyanidin, 7-hydroxy-3',4'-methylenedioxyflavan, quercetin and ellagic acid among the 186 biologically important phenylpropanoids and polyketides as potential lead compounds, which can further be investigated pharmacologically and clinically to formulate therapeutic approaches for the COVID-19.
|
q-bio/0612022
|
Andrei Khrennikov
|
Andrei Khrennikov and Marcus Nilsson
|
A number theoretical observation about the degeneracy of the genetic
code
|
References
| null | null |
Reports MSI, N 06166, Vaxjo University Press (ISSN 1650-2647)
|
q-bio.OT
| null |
We discuss the similarity of the degeneration structure of the genetic code
with a pure number theoretic -- ``divisors code.'' The most interesting thing
about our observation is not that there is a connection between number theory
and the genetic code, but the simplicity of the rule. We hope that the
observation and the naive model presented in this paper will serve for ideas to
other models of the degeneracy of the genetic code. Maybe, the ideas of this
article can also be used in the area of artificial life to syntesize artificial
genetic codes.
|
[
{
"created": "Wed, 13 Dec 2006 15:59:36 GMT",
"version": "v1"
},
{
"created": "Mon, 25 Dec 2006 10:34:48 GMT",
"version": "v2"
}
] |
2007-05-23
|
[
[
"Khrennikov",
"Andrei",
""
],
[
"Nilsson",
"Marcus",
""
]
] |
We discuss the similarity of the degeneration structure of the genetic code with a pure number theoretic -- ``divisors code.'' The most interesting thing about our observation is not that there is a connection between number theory and the genetic code, but the simplicity of the rule. We hope that the observation and the naive model presented in this paper will serve for ideas to other models of the degeneracy of the genetic code. Maybe, the ideas of this article can also be used in the area of artificial life to syntesize artificial genetic codes.
|
1810.00224
|
Luiz Gadelha Jr.
|
Luiz M. R. Gadelha Jr., Pedro C. de Siracusa, Artur Ziviani, Eduardo
Couto Dalcin, Helen Michelle Affe, Marinez Ferreira de Siqueira, Lu\'is
Alexandre Estev\~ao da Silva, Douglas A. Augusto, Eduardo Krempser, Marcia
Chame, Raquel Lopes Costa, Pedro Milet Meirelles, Fabiano Thompson
|
A survey of biodiversity informatics: Concepts, practices, and
challenges
| null |
WIREs Data Mining and Knowledge Discovery (2020)
|
10.1002/widm.1394
| null |
q-bio.PE cs.DB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The unprecedented size of the human population, along with its associated
economic activities, have an ever increasing impact on global environments.
Across the world, countries are concerned about the growing resource
consumption and the capacity of ecosystems to provide them. To effectively
conserve biodiversity, it is essential to make indicators and knowledge openly
available to decision-makers in ways that they can effectively use them. The
development and deployment of mechanisms to produce these indicators depend on
having access to trustworthy data from field surveys and automated sensors,
biological collections, molecular data, and historic academic literature. The
transformation of this raw data into synthesized information that is fit for
use requires going through many refinement steps. The methodologies and
techniques used to manage and analyze this data comprise an area often called
biodiversity informatics (or e-Biodiversity). Biodiversity data follows a life
cycle consisting of planning, collection, certification, description,
preservation, discovery, integration, and analysis. Researchers, whether
producers or consumers of biodiversity data, will likely perform activities
related to at least one of these steps. This article explores each stage of the
life cycle of biodiversity data, discussing its methodologies, tools, and
challenges.
|
[
{
"created": "Sat, 29 Sep 2018 15:41:17 GMT",
"version": "v1"
},
{
"created": "Mon, 7 Dec 2020 11:22:48 GMT",
"version": "v2"
}
] |
2020-12-15
|
[
[
"Gadelha",
"Luiz M. R.",
"Jr."
],
[
"de Siracusa",
"Pedro C.",
""
],
[
"Ziviani",
"Artur",
""
],
[
"Dalcin",
"Eduardo Couto",
""
],
[
"Affe",
"Helen Michelle",
""
],
[
"de Siqueira",
"Marinez Ferreira",
""
],
[
"da Silva",
"Luís Alexandre Estevão",
""
],
[
"Augusto",
"Douglas A.",
""
],
[
"Krempser",
"Eduardo",
""
],
[
"Chame",
"Marcia",
""
],
[
"Costa",
"Raquel Lopes",
""
],
[
"Meirelles",
"Pedro Milet",
""
],
[
"Thompson",
"Fabiano",
""
]
] |
The unprecedented size of the human population, along with its associated economic activities, have an ever increasing impact on global environments. Across the world, countries are concerned about the growing resource consumption and the capacity of ecosystems to provide them. To effectively conserve biodiversity, it is essential to make indicators and knowledge openly available to decision-makers in ways that they can effectively use them. The development and deployment of mechanisms to produce these indicators depend on having access to trustworthy data from field surveys and automated sensors, biological collections, molecular data, and historic academic literature. The transformation of this raw data into synthesized information that is fit for use requires going through many refinement steps. The methodologies and techniques used to manage and analyze this data comprise an area often called biodiversity informatics (or e-Biodiversity). Biodiversity data follows a life cycle consisting of planning, collection, certification, description, preservation, discovery, integration, and analysis. Researchers, whether producers or consumers of biodiversity data, will likely perform activities related to at least one of these steps. This article explores each stage of the life cycle of biodiversity data, discussing its methodologies, tools, and challenges.
|
0901.2227
|
Ellen Baake
|
Florian Lipsmeier, Ellen Baake
|
Rare event simulation for T-cell activation
|
29 pages, 14 figures; J. Stat. Phys., in press
|
J. Stat. Phys. 134 (2009), 537-566
|
10.1007/s10955-008-9672-2
| null |
q-bio.SC math.PR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The problem of \emph{statistical recognition} is considered, as it arises in
immunobiology, namely, the discrimination of foreign antigens against a
background of the body's own molecules. The precise mechanism of this
foreign-self-distinction, though one of the major tasks of the immune system,
continues to be a fundamental puzzle. Recent progress has been made by van den
Berg, Rand, and Burroughs (2001), who modelled the \emph{probabilistic} nature
of the interaction between the relevant cell types, namely, T-cells and
antigen-presenting cells (APCs). Here, the stochasticity is due to the random
sample of antigens present on the surface of every APC, and to the random
receptor type that characterises individual T-cells. It has been shown
previously that this model, though highly idealised, is capable of reproducing
important aspects of the recognition phenomenon, and of explaining them on the
basis of stochastic rare events. These results were obtained with the help of a
refined large deviation theorem and were thus asymptotic in nature. Simulations
have, so far, been restricted to the straightforward simple sampling approach,
which does not allow for sample sizes large enough to address more detailed
questions. Building on the available large deviation results, we develop an
importance sampling technique that allows for a convenient exploration of the
relevant tail events by means of simulation. With its help, we investigate the
mechanism of statistical recognition in some depth. In particular, we
illustrate how a foreign antigen can stand out against the self background if
it is present in sufficiently many copies, although no \emph{a priori}
difference between self and nonself is built into the model.
|
[
{
"created": "Thu, 15 Jan 2009 10:52:25 GMT",
"version": "v1"
}
] |
2009-09-30
|
[
[
"Lipsmeier",
"Florian",
""
],
[
"Baake",
"Ellen",
""
]
] |
The problem of \emph{statistical recognition} is considered, as it arises in immunobiology, namely, the discrimination of foreign antigens against a background of the body's own molecules. The precise mechanism of this foreign-self-distinction, though one of the major tasks of the immune system, continues to be a fundamental puzzle. Recent progress has been made by van den Berg, Rand, and Burroughs (2001), who modelled the \emph{probabilistic} nature of the interaction between the relevant cell types, namely, T-cells and antigen-presenting cells (APCs). Here, the stochasticity is due to the random sample of antigens present on the surface of every APC, and to the random receptor type that characterises individual T-cells. It has been shown previously that this model, though highly idealised, is capable of reproducing important aspects of the recognition phenomenon, and of explaining them on the basis of stochastic rare events. These results were obtained with the help of a refined large deviation theorem and were thus asymptotic in nature. Simulations have, so far, been restricted to the straightforward simple sampling approach, which does not allow for sample sizes large enough to address more detailed questions. Building on the available large deviation results, we develop an importance sampling technique that allows for a convenient exploration of the relevant tail events by means of simulation. With its help, we investigate the mechanism of statistical recognition in some depth. In particular, we illustrate how a foreign antigen can stand out against the self background if it is present in sufficiently many copies, although no \emph{a priori} difference between self and nonself is built into the model.
|
q-bio/0504017
|
Giovanni Meacci
|
G. Meacci, K. Kruse
|
Min-oscillations in Escherichia coli induced by interactions of
membrane-bound proteins
|
17 pages, 5 figures. Submitted to Physical Biology
|
Phys. Biol. 2 (2005) 89-97
|
10.1088/1478-3975/2/2/002
| null |
q-bio.SC cond-mat.stat-mech physics.bio-ph
| null |
During division it is of primary importance for a cell to correctly determine
the site of cleavage. The bacterium Escherichia coli divides in the center,
producing two daughter cells of equal size. Selection of the center as the
correct division site is in part achieved by the Min-proteins. They oscillate
between the two cell poles and thereby prevent division at these locations.
Here, a phenomenological description for these oscillations is presented, where
lateral interactions between proteins on the cell membrane play a key role.
Solutions to the dynamic equations are compared to experimental findings. In
particular, the temporal period of the oscillations is measured as a function
of the cell length and found to be compatible with the theoretical prediction.
|
[
{
"created": "Wed, 13 Apr 2005 15:27:31 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Meacci",
"G.",
""
],
[
"Kruse",
"K.",
""
]
] |
During division it is of primary importance for a cell to correctly determine the site of cleavage. The bacterium Escherichia coli divides in the center, producing two daughter cells of equal size. Selection of the center as the correct division site is in part achieved by the Min-proteins. They oscillate between the two cell poles and thereby prevent division at these locations. Here, a phenomenological description for these oscillations is presented, where lateral interactions between proteins on the cell membrane play a key role. Solutions to the dynamic equations are compared to experimental findings. In particular, the temporal period of the oscillations is measured as a function of the cell length and found to be compatible with the theoretical prediction.
|
2103.09709
|
Neta Maimon
|
Neta B. Maimon, Dominique Lamy, and Zohar Eitan
|
Do Picardy thirds smile? Tonal hierarchy and tonal valence: explicit and
implicit measures
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by/4.0/
|
Western tonality provides a hierarchy of stability among melodic
scale-degrees, from the maximally stable tonic to unstable chromatic notes.
Tonal stability has been linked to emotion, yet systematic investigations of
the associations between the hierarchy of melodic scale-degrees and perceived
emotional valence are lacking. Here, we examined such associations in three
experiments, in musicians and in non-musicians. We used an explicit task, in
which participants matched probe tones following key-establishing sequences to
facial expressions ranging from sad to happy, and an implicit speeded task, a
variant of the Implicit Association Test. Stabler scale-degrees were associated
with more positive valence in all experiments, for both musicians and
nonmusicians. This notwithstanding, results significantly differed from those
of a comparable goodness-of-fit task, suggesting that perceived tonal valence
is not reducible to tonal fit. Comparisons of the explicit and implicit
measures suggest that associations of tonality and emotional valence may rely
on two distinct mechanisms, one mediated by conceptual musical knowledge and
conscious decisional processes, the other - largely by non-conceptual and
involuntary processes. The joint experimental paradigms introduced here may
help mapping additional connotative meanings, both emotional and cross-modal,
embedded in tonal structure, thus suggesting how extra-musical meanings are
conveyed to listeners through musical syntax.
|
[
{
"created": "Wed, 17 Mar 2021 15:08:18 GMT",
"version": "v1"
}
] |
2021-03-18
|
[
[
"Maimon",
"Neta B.",
""
],
[
"Lamy",
"Dominique",
""
],
[
"Eitan",
"Zohar",
""
]
] |
Western tonality provides a hierarchy of stability among melodic scale-degrees, from the maximally stable tonic to unstable chromatic notes. Tonal stability has been linked to emotion, yet systematic investigations of the associations between the hierarchy of melodic scale-degrees and perceived emotional valence are lacking. Here, we examined such associations in three experiments, in musicians and in non-musicians. We used an explicit task, in which participants matched probe tones following key-establishing sequences to facial expressions ranging from sad to happy, and an implicit speeded task, a variant of the Implicit Association Test. Stabler scale-degrees were associated with more positive valence in all experiments, for both musicians and nonmusicians. This notwithstanding, results significantly differed from those of a comparable goodness-of-fit task, suggesting that perceived tonal valence is not reducible to tonal fit. Comparisons of the explicit and implicit measures suggest that associations of tonality and emotional valence may rely on two distinct mechanisms, one mediated by conceptual musical knowledge and conscious decisional processes, the other - largely by non-conceptual and involuntary processes. The joint experimental paradigms introduced here may help mapping additional connotative meanings, both emotional and cross-modal, embedded in tonal structure, thus suggesting how extra-musical meanings are conveyed to listeners through musical syntax.
|
1303.6227
|
Eric Gamazon
|
Eric R. Gamazon, Hae Kyung Im, Chunyu Liu, Members of the Bipolar
Disorder Genome Study (BiGS) Consortium, Dan L. Nicolae, Nancy J. Cox
|
The Convergence of eQTL Mapping, Heritability Estimation and Polygenic
Modeling: Emerging Spectrum of Risk Variation in Bipolar Disorder
| null | null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
It is widely held that a substantial genetic component underlies Bipolar
Disorder (BD) and other neuropsychiatric disease traits. Recent efforts have
been aimed at understanding the genetic basis of disease susceptibility, with
genome-wide association studies (GWAS) unveiling some promising associations.
Nevertheless, the genetic etiology of BD remains elusive with a substantial
proportion of the heritability - which has been estimated to be 80% based on
twin and family studies - unaccounted for by the specific genetic variants
identified by large-scale GWAS. Furthermore, functional understanding of
associated loci generally lags discovery. Studies we report here provide
considerable support to the claim that substantially more remains to be gained
from GWAS on the genetic mechanisms underlying BD susceptibility, and that a
large proportion of the variation in disease risk may be uncovered through
integrative functional genomic approaches. We combine recent analytic advances
in heritability estimation and polygenic modeling and leverage recent
technological advances in the generation of -omics data to evaluate the nature
and scale of the contribution of functional classes of genetic variation to a
relatively intractable disorder. We identified cis eQTLs in cerebellum and
parietal cortex that capture more than half of the total heritability
attributable to SNPs interrogated through GWAS and showed that eQTL-based
heritability estimation is highly tissue-dependent. Our findings show that a
much greater resolution may be attained than has been reported thus far on the
number of common loci that capture a substantial proportion of the heritability
to disease risk and that the functional nature of contributory loci may be
clarified en masse.
|
[
{
"created": "Mon, 25 Mar 2013 17:43:16 GMT",
"version": "v1"
},
{
"created": "Fri, 29 Mar 2013 04:45:06 GMT",
"version": "v2"
}
] |
2013-04-01
|
[
[
"Gamazon",
"Eric R.",
"",
"BiGS"
],
[
"Im",
"Hae Kyung",
"",
"BiGS"
],
[
"Liu",
"Chunyu",
"",
"BiGS"
],
[
"Study",
"Members of the Bipolar Disorder Genome",
"",
"BiGS"
],
[
"Consortium",
"",
""
],
[
"Nicolae",
"Dan L.",
""
],
[
"Cox",
"Nancy J.",
""
]
] |
It is widely held that a substantial genetic component underlies Bipolar Disorder (BD) and other neuropsychiatric disease traits. Recent efforts have been aimed at understanding the genetic basis of disease susceptibility, with genome-wide association studies (GWAS) unveiling some promising associations. Nevertheless, the genetic etiology of BD remains elusive with a substantial proportion of the heritability - which has been estimated to be 80% based on twin and family studies - unaccounted for by the specific genetic variants identified by large-scale GWAS. Furthermore, functional understanding of associated loci generally lags discovery. Studies we report here provide considerable support to the claim that substantially more remains to be gained from GWAS on the genetic mechanisms underlying BD susceptibility, and that a large proportion of the variation in disease risk may be uncovered through integrative functional genomic approaches. We combine recent analytic advances in heritability estimation and polygenic modeling and leverage recent technological advances in the generation of -omics data to evaluate the nature and scale of the contribution of functional classes of genetic variation to a relatively intractable disorder. We identified cis eQTLs in cerebellum and parietal cortex that capture more than half of the total heritability attributable to SNPs interrogated through GWAS and showed that eQTL-based heritability estimation is highly tissue-dependent. Our findings show that a much greater resolution may be attained than has been reported thus far on the number of common loci that capture a substantial proportion of the heritability to disease risk and that the functional nature of contributory loci may be clarified en masse.
|
2302.03250
|
Yuan Wang
|
Xingpei Zhao, Nicholas Riccardi, Rutvik H. Desai, Dirk-Bart den Ouden,
Julius Fridriksson, Yuan Wang
|
Network-based Statistics Distinguish Anomic and Broca Aphasia
| null | null | null | null |
q-bio.NC stat.AP
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Aphasia is a speech-language impairment commonly caused by damage to the left
hemisphere. Due to the complexity of speech-language processing, the neural
mechanisms that underpin various symptoms between different types of aphasia
are still not fully understood. We used the network-based statistic method to
identify distinct subnetwork(s) of connections differentiating the
resting-state functional networks of the anomic and Broca groups. We identified
one such subnetwork that mainly involved the brain regions in the premotor,
primary motor, primary auditory, and primary sensory cortices in both
hemispheres. The majority of connections in the subnetwork were weaker in the
Broca group than the anomic group. The network properties of the subnetwork
were examined through complex network measures, which indicated that the
regions in the superior temporal gyrus and auditory cortex bilaterally exhibit
intensive interaction, and primary motor, premotor and primary sensory cortices
in the left hemisphere play an important role in information flow and overall
communication efficiency. These findings underlied articulatory difficulties
and reduced repetition performance in Broca aphasia, which are rarely observed
in anomic aphasia. This research provides novel findings into the resting-state
brain network differences between groups of individuals with anomic and Broca
aphasia. We identified a subnetwork of, rather than isolated, connections that
statistically differentiate the resting-state brain networks of the two groups,
in comparison with standard lesion symptom mapping results that yield isolated
connections.
|
[
{
"created": "Tue, 7 Feb 2023 04:33:18 GMT",
"version": "v1"
},
{
"created": "Fri, 17 Feb 2023 20:45:15 GMT",
"version": "v2"
}
] |
2023-02-21
|
[
[
"Zhao",
"Xingpei",
""
],
[
"Riccardi",
"Nicholas",
""
],
[
"Desai",
"Rutvik H.",
""
],
[
"Ouden",
"Dirk-Bart den",
""
],
[
"Fridriksson",
"Julius",
""
],
[
"Wang",
"Yuan",
""
]
] |
Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. Due to the complexity of speech-language processing, the neural mechanisms that underpin various symptoms between different types of aphasia are still not fully understood. We used the network-based statistic method to identify distinct subnetwork(s) of connections differentiating the resting-state functional networks of the anomic and Broca groups. We identified one such subnetwork that mainly involved the brain regions in the premotor, primary motor, primary auditory, and primary sensory cortices in both hemispheres. The majority of connections in the subnetwork were weaker in the Broca group than the anomic group. The network properties of the subnetwork were examined through complex network measures, which indicated that the regions in the superior temporal gyrus and auditory cortex bilaterally exhibit intensive interaction, and primary motor, premotor and primary sensory cortices in the left hemisphere play an important role in information flow and overall communication efficiency. These findings underlied articulatory difficulties and reduced repetition performance in Broca aphasia, which are rarely observed in anomic aphasia. This research provides novel findings into the resting-state brain network differences between groups of individuals with anomic and Broca aphasia. We identified a subnetwork of, rather than isolated, connections that statistically differentiate the resting-state brain networks of the two groups, in comparison with standard lesion symptom mapping results that yield isolated connections.
|
1410.8826
|
Adam Marblestone
|
Gary F. Marcus and Adam H. Marblestone and Thomas L. Dean
|
Frequently Asked Questions for: The Atoms of Neural Computation
|
Frequently Asked Questions (FAQ) for Marcus, Marblestone and Dean.
"The Atoms of Neural Computation". Science. 31 OCTOBER 2014. VOL 346 ISSUE
6209
| null |
10.1126/science.1261661
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Based on a survey of the literature, we attempt to answer Frequently Asked
Questions on issues of cortical uniformity vs. non-uniformity, the neural
mechanisms of symbolic variable binding, and other issues highlighted in
(Marcus, Marblestone and Dean. "The Atoms of Neural Computation". Science. 31
October 2014. Vol 346. Issue 6209).
|
[
{
"created": "Fri, 31 Oct 2014 17:38:34 GMT",
"version": "v1"
}
] |
2014-11-03
|
[
[
"Marcus",
"Gary F.",
""
],
[
"Marblestone",
"Adam H.",
""
],
[
"Dean",
"Thomas L.",
""
]
] |
Based on a survey of the literature, we attempt to answer Frequently Asked Questions on issues of cortical uniformity vs. non-uniformity, the neural mechanisms of symbolic variable binding, and other issues highlighted in (Marcus, Marblestone and Dean. "The Atoms of Neural Computation". Science. 31 October 2014. Vol 346. Issue 6209).
|
1202.0433
|
Jens Karschau
|
Jens Karschau, J. Julian Blow, Alessandro P. S. de Moura
|
Optimal Placement of Origins for DNA Replication
|
5 pages, 3 figures
|
Phys. Rev. Lett. 108, 058101 (2012)
|
10.1103/PhysRevLett.108.058101
| null |
q-bio.QM cond-mat.stat-mech physics.bio-ph q-bio.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
DNA replication is an essential process in biology and its timing must be
robust so that cells can divide properly. Random fluctuations in the formation
of replication starting points, called origins, and the subsequent activation
of proteins lead to variations in the replication time. We analyse these
stochastic properties of DNA and derive the positions of origins corresponding
to the minimum replication time. We show that under some conditions the
minimization of replication time leads to the grouping of origins, and relate
this to experimental data in a number of species showing origin grouping.
|
[
{
"created": "Thu, 2 Feb 2012 13:46:26 GMT",
"version": "v1"
}
] |
2012-02-03
|
[
[
"Karschau",
"Jens",
""
],
[
"Blow",
"J. Julian",
""
],
[
"de Moura",
"Alessandro P. S.",
""
]
] |
DNA replication is an essential process in biology and its timing must be robust so that cells can divide properly. Random fluctuations in the formation of replication starting points, called origins, and the subsequent activation of proteins lead to variations in the replication time. We analyse these stochastic properties of DNA and derive the positions of origins corresponding to the minimum replication time. We show that under some conditions the minimization of replication time leads to the grouping of origins, and relate this to experimental data in a number of species showing origin grouping.
|
1907.02160
|
Mason A. Porter
|
Cameron L. Hall, Mason A. Porter, and Marian S. Dawkins
|
Dominance, Sharing, and Assessment in an Iterated Hawk--Dove Game
| null | null | null | null |
q-bio.PE math.DS nlin.AO physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Animals use a wide variety of strategies to reduce or avoid aggression in
conflicts over resources. These strategies range from sharing resources without
outward signs of conflict to the development of dominance hierarchies, in which
initial fighting is followed by the submission of subordinates. Although models
have been developed to analyze specific strategies for resolving conflicts over
resources, little work has focused on trying to understand why particular
strategies are more likely to arise in certain situations. In this paper, we
use a model based on an iterated Hawk--Dove game to analyze how resource
holding potentials (RHPs) and other factors affect whether sharing, dominance
relationships, or other behaviours are evolutionarily stable. We find through
extensive numerical simulations that sharing is stable only when the cost of
fighting is low and the animals in a contest have similar RHPs, whereas
dominance relationships are stable in most other situations. We also explore
what happens when animals are unable to assess each other's RHPs without
fighting, and we compare a range of strategies for this problem using
simulations. We find (1) that the most successful strategies involve a limited
period of assessment followed by a stable relationship in which fights are
avoided and (2) that the duration of assessment depends both on the costliness
of fighting and on the difference between the animals' RHPs. Along with our
direct work on modeling and simulations, we develop extensive software to
facilitate further testing; it is available at
\url{https://bitbucket.org/CameronLHall/dominancesharingassessmentmatlab/}.
|
[
{
"created": "Wed, 3 Jul 2019 23:11:05 GMT",
"version": "v1"
},
{
"created": "Thu, 31 Oct 2019 04:22:31 GMT",
"version": "v2"
}
] |
2019-11-01
|
[
[
"Hall",
"Cameron L.",
""
],
[
"Porter",
"Mason A.",
""
],
[
"Dawkins",
"Marian S.",
""
]
] |
Animals use a wide variety of strategies to reduce or avoid aggression in conflicts over resources. These strategies range from sharing resources without outward signs of conflict to the development of dominance hierarchies, in which initial fighting is followed by the submission of subordinates. Although models have been developed to analyze specific strategies for resolving conflicts over resources, little work has focused on trying to understand why particular strategies are more likely to arise in certain situations. In this paper, we use a model based on an iterated Hawk--Dove game to analyze how resource holding potentials (RHPs) and other factors affect whether sharing, dominance relationships, or other behaviours are evolutionarily stable. We find through extensive numerical simulations that sharing is stable only when the cost of fighting is low and the animals in a contest have similar RHPs, whereas dominance relationships are stable in most other situations. We also explore what happens when animals are unable to assess each other's RHPs without fighting, and we compare a range of strategies for this problem using simulations. We find (1) that the most successful strategies involve a limited period of assessment followed by a stable relationship in which fights are avoided and (2) that the duration of assessment depends both on the costliness of fighting and on the difference between the animals' RHPs. Along with our direct work on modeling and simulations, we develop extensive software to facilitate further testing; it is available at \url{https://bitbucket.org/CameronLHall/dominancesharingassessmentmatlab/}.
|
2103.03816
|
Stephan Meighen-Berger
|
Stephan Meighen-Berger, Li Ruohan, Golo Wimmer
|
Bioluminescence modeling for deep sea experiments
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We develop a modeling framework for bioluminescence light found in the deep
sea near neutrino telescopes by combining a hydrodynamic model with a
stochastic one. The bioluminescence is caused by organisms when exposed to a
non-constant water flow, such as past the neutrino telescopes. We model the
flow using the incompressible Navier-Stokes equations for Reynolds numbers
between 4000 and 23000. The discretization relies on a finite element method
which includes upwind-stabilization for the velocity field. On top of the flow
model, we simulate a population of random microscopic organisms. Their movement
and emission are stochastic processes which we model using Monte Carlo methods.
We observe unique time-series for the photon counts depending on the flow
velocity and detector specifications. This opens up the possibility of
categorizing organisms using neutrino detectors. We show that the average
light-yield and pulse shapes require precise flow modeling, while the emission
timing is chaotic. From this we construct a fast modeling scheme, requiring
only a subset of computationally expensive flow and population modeling.
|
[
{
"created": "Tue, 9 Feb 2021 09:08:52 GMT",
"version": "v1"
},
{
"created": "Mon, 28 Jun 2021 21:04:51 GMT",
"version": "v2"
}
] |
2021-06-30
|
[
[
"Meighen-Berger",
"Stephan",
""
],
[
"Ruohan",
"Li",
""
],
[
"Wimmer",
"Golo",
""
]
] |
We develop a modeling framework for bioluminescence light found in the deep sea near neutrino telescopes by combining a hydrodynamic model with a stochastic one. The bioluminescence is caused by organisms when exposed to a non-constant water flow, such as past the neutrino telescopes. We model the flow using the incompressible Navier-Stokes equations for Reynolds numbers between 4000 and 23000. The discretization relies on a finite element method which includes upwind-stabilization for the velocity field. On top of the flow model, we simulate a population of random microscopic organisms. Their movement and emission are stochastic processes which we model using Monte Carlo methods. We observe unique time-series for the photon counts depending on the flow velocity and detector specifications. This opens up the possibility of categorizing organisms using neutrino detectors. We show that the average light-yield and pulse shapes require precise flow modeling, while the emission timing is chaotic. From this we construct a fast modeling scheme, requiring only a subset of computationally expensive flow and population modeling.
|
1407.3432
|
Randall O'Reilly
|
Randall C. O'Reilly and Dean Wyatte and John Rohrlich
|
Learning Through Time in the Thalamocortical Loops
|
37 pages, 11 figures. arXiv admin note: text overlap with
arXiv:1112.0778 by other authors
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We present a comprehensive, novel framework for understanding how the
neocortex, including the thalamocortical loops through the deep layers, can
support a temporal context representation in the service of predictive
learning. Many have argued that predictive learning provides a compelling,
powerful source of learning signals to drive the development of human
intelligence: if we constantly predict what will happen next, and learn based
on the discrepancies from our predictions (error-driven learning), then we can
learn to improve our predictions by developing internal representations that
capture the regularities of the environment (e.g., physical laws governing the
time-evolution of object motions). Our version of this idea builds upon
existing work with simple recurrent networks (SRN's), which have a
discretely-updated temporal context representations that are a direct copy of
the prior internal state representation. We argue that this discretization of
temporal context updating has a number of important computational and
functional advantages, and further show how the strong alpha-frequency (10hz,
100ms cycle time) oscillations in the posterior neocortex could reflect this
temporal context updating. We examine a wide range of data from biology to
behavior through the lens of this LeabraTI model, and find that it provides a
unified account of a number of otherwise disconnected findings, all of which
converge to support this new model of neocortical learning and processing. We
describe an implemented model showing how predictive learning of tumbling
object trajectories can facilitate object recognition with cluttered
backgrounds.
|
[
{
"created": "Sun, 13 Jul 2014 05:43:44 GMT",
"version": "v1"
}
] |
2014-07-15
|
[
[
"O'Reilly",
"Randall C.",
""
],
[
"Wyatte",
"Dean",
""
],
[
"Rohrlich",
"John",
""
]
] |
We present a comprehensive, novel framework for understanding how the neocortex, including the thalamocortical loops through the deep layers, can support a temporal context representation in the service of predictive learning. Many have argued that predictive learning provides a compelling, powerful source of learning signals to drive the development of human intelligence: if we constantly predict what will happen next, and learn based on the discrepancies from our predictions (error-driven learning), then we can learn to improve our predictions by developing internal representations that capture the regularities of the environment (e.g., physical laws governing the time-evolution of object motions). Our version of this idea builds upon existing work with simple recurrent networks (SRN's), which have a discretely-updated temporal context representations that are a direct copy of the prior internal state representation. We argue that this discretization of temporal context updating has a number of important computational and functional advantages, and further show how the strong alpha-frequency (10hz, 100ms cycle time) oscillations in the posterior neocortex could reflect this temporal context updating. We examine a wide range of data from biology to behavior through the lens of this LeabraTI model, and find that it provides a unified account of a number of otherwise disconnected findings, all of which converge to support this new model of neocortical learning and processing. We describe an implemented model showing how predictive learning of tumbling object trajectories can facilitate object recognition with cluttered backgrounds.
|
1304.6394
|
Alain Barrat
|
Anna Machens, Francesco Gesualdo, Caterina Rizzo, Alberto E Tozzi,
Alain Barrat, Ciro Cattuto
|
An infectious disease model on empirical networks of human contact:
bridging the gap between dynamic network data and contact matrices
| null |
BMC Infectious Diseases 13:185 (2013)
|
10.1186/1471-2334-13-185
| null |
q-bio.PE physics.comp-ph physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The integration of empirical data in computational frameworks to model the
spread of infectious diseases poses challenges that are becoming pressing with
the increasing availability of high-resolution information on human mobility
and contacts. This deluge of data has the potential to revolutionize the
computational efforts aimed at simulating scenarios and designing containment
strategies. However, the integration of detailed data sources yields models
that are less transparent and general. Hence, given a specific disease model,
it is crucial to assess which representations of the raw data strike the best
balance between simplicity and detail. We consider high-resolution data on the
face-to-face interactions of individuals in a hospital ward, obtained by using
wearable proximity sensors. We simulate the spread of a disease in this
community by using an SEIR model on top of different mathematical
representations of the contact patterns. We show that a contact matrix that
only contains average contact durations fails to reproduce the size of the
epidemic obtained with the high-resolution contact data and also to identify
the most at-risk classes. We introduce a contact matrix of probability
distributions that takes into account the heterogeneity of contact durations
between (and within) classes of individuals, and we show that this
representation yields a good approximation of the epidemic spreading properties
obtained by using the high-resolution data. Our results mark a step towards the
definition of synopses of high-resolution dynamic contact networks, providing a
compact representation of contact patterns that can correctly inform
computational models designed to discover risk groups and evaluate containment
policies. We show that this novel kind of representation can preserve in
simulation quantitative features of the epidemics that are crucial for their
study and management.
|
[
{
"created": "Tue, 23 Apr 2013 19:55:32 GMT",
"version": "v1"
}
] |
2013-04-24
|
[
[
"Machens",
"Anna",
""
],
[
"Gesualdo",
"Francesco",
""
],
[
"Rizzo",
"Caterina",
""
],
[
"Tozzi",
"Alberto E",
""
],
[
"Barrat",
"Alain",
""
],
[
"Cattuto",
"Ciro",
""
]
] |
The integration of empirical data in computational frameworks to model the spread of infectious diseases poses challenges that are becoming pressing with the increasing availability of high-resolution information on human mobility and contacts. This deluge of data has the potential to revolutionize the computational efforts aimed at simulating scenarios and designing containment strategies. However, the integration of detailed data sources yields models that are less transparent and general. Hence, given a specific disease model, it is crucial to assess which representations of the raw data strike the best balance between simplicity and detail. We consider high-resolution data on the face-to-face interactions of individuals in a hospital ward, obtained by using wearable proximity sensors. We simulate the spread of a disease in this community by using an SEIR model on top of different mathematical representations of the contact patterns. We show that a contact matrix that only contains average contact durations fails to reproduce the size of the epidemic obtained with the high-resolution contact data and also to identify the most at-risk classes. We introduce a contact matrix of probability distributions that takes into account the heterogeneity of contact durations between (and within) classes of individuals, and we show that this representation yields a good approximation of the epidemic spreading properties obtained by using the high-resolution data. Our results mark a step towards the definition of synopses of high-resolution dynamic contact networks, providing a compact representation of contact patterns that can correctly inform computational models designed to discover risk groups and evaluate containment policies. We show that this novel kind of representation can preserve in simulation quantitative features of the epidemics that are crucial for their study and management.
|
1605.06176
|
Bernal Morera MSc
|
Bernal Morera-Brenes, Mauricio Melendez-Obando
|
The genealogy of Maria de Aguilar: evidence of admixture in the early
Spanish Colony in Costa Rica
|
12 pages, 2 figures, in Spanish
|
Cuadernos de Investigacion 2 (1), 33-43. 2010
| null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
During long time, historians and genealogists have interpreted that the elite
that emerged during the Spanish Conquest was almost exclusively European. We
reconstructed a deep matrilineal genealogy which includes recent Costa Rican
ex-presidents and religious authorities back to their ancestors at the early
17th century, and compared their historic ethnic affinities with genetic
mitochondrial evidence of some living descendents. The observed DNA lineage has
an Amerindian ancestry. Such results point out that an Amerindian gene flow had
occurred into the Spanish group during the first generations of colonial
society. This conclusion do not support the current idea that the Spanish elite
avoided interethnic marriages.
|
[
{
"created": "Thu, 19 May 2016 23:45:40 GMT",
"version": "v1"
}
] |
2016-05-23
|
[
[
"Morera-Brenes",
"Bernal",
""
],
[
"Melendez-Obando",
"Mauricio",
""
]
] |
During long time, historians and genealogists have interpreted that the elite that emerged during the Spanish Conquest was almost exclusively European. We reconstructed a deep matrilineal genealogy which includes recent Costa Rican ex-presidents and religious authorities back to their ancestors at the early 17th century, and compared their historic ethnic affinities with genetic mitochondrial evidence of some living descendents. The observed DNA lineage has an Amerindian ancestry. Such results point out that an Amerindian gene flow had occurred into the Spanish group during the first generations of colonial society. This conclusion do not support the current idea that the Spanish elite avoided interethnic marriages.
|
1309.0670
|
Surojit Biswas
|
Surojit Biswas, Yash N. Agrawal, Tatiana S. Mucyn, Jeffery L. Dangl,
Corbin D. Jones
|
Biological Averaging in RNA-Seq
| null | null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
RNA-seq has become a de facto standard for measuring gene expression.
Traditionally, RNA-seq experiments are mathematically averaged -- they sequence
the mRNA of individuals from different treatment groups, hoping to correlate
phenotype with differences in arithmetic read count averages at shared loci of
interest. Alternatively, the tissue from the same individuals may be pooled
prior to sequencing in what we refer to as a biologically averaged design. As
mathematical averaging sequences all individuals it controls for both
biological and technical variation; however, is the statistical resolution
gained always worth the additional cost? To compare biological and mathematical
averaging, we examined theoretical and empirical estimates of statistical
efficiency and relative cost efficiency. Though less efficient at a fixed
sample size, we found that biological averaging can be more cost efficient than
mathematical averaging. With this motivation, we developed a differential
expression classifier, ICRBC, that can detect alternatively expressed genes
between biologically averaged samples. In simulation studies, we found that
biological averaging and subsequent analysis with our classifier performed
comparably to existing methods, such as ASC, edgeR, and DESeq, especially when
individuals were pooled evenly and less than 20% of the regulome was expected
to be differentially regulated. In two technically distinct mouse datasets and
one plant dataset, we found that our method was over 87% concordant with edgeR
for the 100 most significant features. We therefore conclude biological
averaging may sufficiently control biological variation to a level that
differences in gene expression may be detectable. In such situations, ICRBC can
enable reliable exploratory analysis at a fraction of the cost, especially when
interest lies in the most differentially expressed loci.
|
[
{
"created": "Tue, 3 Sep 2013 13:37:47 GMT",
"version": "v1"
},
{
"created": "Wed, 4 Sep 2013 19:28:49 GMT",
"version": "v2"
}
] |
2013-09-05
|
[
[
"Biswas",
"Surojit",
""
],
[
"Agrawal",
"Yash N.",
""
],
[
"Mucyn",
"Tatiana S.",
""
],
[
"Dangl",
"Jeffery L.",
""
],
[
"Jones",
"Corbin D.",
""
]
] |
RNA-seq has become a de facto standard for measuring gene expression. Traditionally, RNA-seq experiments are mathematically averaged -- they sequence the mRNA of individuals from different treatment groups, hoping to correlate phenotype with differences in arithmetic read count averages at shared loci of interest. Alternatively, the tissue from the same individuals may be pooled prior to sequencing in what we refer to as a biologically averaged design. As mathematical averaging sequences all individuals it controls for both biological and technical variation; however, is the statistical resolution gained always worth the additional cost? To compare biological and mathematical averaging, we examined theoretical and empirical estimates of statistical efficiency and relative cost efficiency. Though less efficient at a fixed sample size, we found that biological averaging can be more cost efficient than mathematical averaging. With this motivation, we developed a differential expression classifier, ICRBC, that can detect alternatively expressed genes between biologically averaged samples. In simulation studies, we found that biological averaging and subsequent analysis with our classifier performed comparably to existing methods, such as ASC, edgeR, and DESeq, especially when individuals were pooled evenly and less than 20% of the regulome was expected to be differentially regulated. In two technically distinct mouse datasets and one plant dataset, we found that our method was over 87% concordant with edgeR for the 100 most significant features. We therefore conclude biological averaging may sufficiently control biological variation to a level that differences in gene expression may be detectable. In such situations, ICRBC can enable reliable exploratory analysis at a fraction of the cost, especially when interest lies in the most differentially expressed loci.
|
1506.04458
|
Tomasz Rutkowski
|
Kensuke Shimizu, Shoji Makino, and Tomasz M. Rutkowski
|
Inter-stimulus Interval Study for the Tactile Point-pressure
Brain-computer Interface
|
4 pages, 5 figures, accepted for EMBC 2015, IEEE copyright
| null |
10.1109/EMBC.2015.7318756
| null |
q-bio.NC cs.HC
|
http://creativecommons.org/licenses/by-nc-sa/3.0/
|
The paper presents a study of an inter-stimulus interval (ISI) influence on a
tactile point-pressure stimulus-based brain-computer interface's (tpBCI)
classification accuracy. A novel tactile pressure generating tpBCI stimulator
is also discussed, which is based on a three-by-three pins' matrix prototype.
The six pin-linear patterns are presented to the user's palm during the online
tpBCI experiments in an oddball style paradigm allowing for "the aha-responses"
elucidation, within the event related potential (ERP). A subsequent
classification accuracies' comparison is discussed based on two ISI settings in
an online tpBCI application. A research hypothesis of classification
accuracies' non-significant differences with various ISIs is confirmed based on
the two settings of 120 ms and 300 ms, as well as with various numbers of ERP
response averaging scenarios.
|
[
{
"created": "Mon, 15 Jun 2015 02:30:36 GMT",
"version": "v1"
}
] |
2016-11-17
|
[
[
"Shimizu",
"Kensuke",
""
],
[
"Makino",
"Shoji",
""
],
[
"Rutkowski",
"Tomasz M.",
""
]
] |
The paper presents a study of an inter-stimulus interval (ISI) influence on a tactile point-pressure stimulus-based brain-computer interface's (tpBCI) classification accuracy. A novel tactile pressure generating tpBCI stimulator is also discussed, which is based on a three-by-three pins' matrix prototype. The six pin-linear patterns are presented to the user's palm during the online tpBCI experiments in an oddball style paradigm allowing for "the aha-responses" elucidation, within the event related potential (ERP). A subsequent classification accuracies' comparison is discussed based on two ISI settings in an online tpBCI application. A research hypothesis of classification accuracies' non-significant differences with various ISIs is confirmed based on the two settings of 120 ms and 300 ms, as well as with various numbers of ERP response averaging scenarios.
|
0707.3464
|
Emmanuel Tannenbaum
|
Emmanuel Tannenbaum
|
A comparison of three replication strategies in complex multicellular
organisms: Asexual replication, sexual replication with identical gametes,
and sexual replication with distinct sperm and egg gametes
|
18 pages, figures included with journal submission
| null |
10.1103/PhysRevE.77.011915
| null |
q-bio.PE
| null |
This paper studies the mutation-selection balance in three simplified
replication models. The first model considers a population of organisms
replicating via the production of asexual spores. The second model considers a
sexually replicating population that produces identical gametes. The third
model considers a sexually replicating population that produces distinct sperm
and egg gametes. All models assume diploid organisms whose genomes consist of
two chromosomes, each of which is taken to be functional if equal to some
master sequence, and defective otherwise. In the asexual population, the
asexual diploid spores develop directly into adult organisms. In the sexual
populations, the haploid gametes enter a haploid pool, where they may fuse with
other haploids. The resulting immature diploid organisms then proceed to
develop into mature organisms. Based on an analysis of all three models, we
find that, as organism size increases, a sexually replicating population can
only outcompete an asexually replicating population if the adult organisms
produce distinct sperm and egg gametes. A sexual replication strategy that is
based on the production of large numbers of sperm cells to fertilize a small
number of eggs is found to be necessary in order to maintain a sufficiently low
cost for sex for the strategy to be selected for over a purely asexual
strategy. We discuss the usefulness of this model in understanding the
evolution and maintenance of sexual replication as the preferred replication
strategy in complex, multicellular organisms.
|
[
{
"created": "Mon, 23 Jul 2007 23:12:52 GMT",
"version": "v1"
}
] |
2009-11-13
|
[
[
"Tannenbaum",
"Emmanuel",
""
]
] |
This paper studies the mutation-selection balance in three simplified replication models. The first model considers a population of organisms replicating via the production of asexual spores. The second model considers a sexually replicating population that produces identical gametes. The third model considers a sexually replicating population that produces distinct sperm and egg gametes. All models assume diploid organisms whose genomes consist of two chromosomes, each of which is taken to be functional if equal to some master sequence, and defective otherwise. In the asexual population, the asexual diploid spores develop directly into adult organisms. In the sexual populations, the haploid gametes enter a haploid pool, where they may fuse with other haploids. The resulting immature diploid organisms then proceed to develop into mature organisms. Based on an analysis of all three models, we find that, as organism size increases, a sexually replicating population can only outcompete an asexually replicating population if the adult organisms produce distinct sperm and egg gametes. A sexual replication strategy that is based on the production of large numbers of sperm cells to fertilize a small number of eggs is found to be necessary in order to maintain a sufficiently low cost for sex for the strategy to be selected for over a purely asexual strategy. We discuss the usefulness of this model in understanding the evolution and maintenance of sexual replication as the preferred replication strategy in complex, multicellular organisms.
|
1405.3293
|
Krishna Garikipati
|
Kristen L. Mills, Ralf Kemkemer, Shiva Rudraraju and Krishna
Garikipati
|
Elastic free energy drives the shape of prevascular solid tumors
|
Six figures in main text. Supporting Information with 6 additional
figures
| null |
10.1371/journal.pone.0103245
| null |
q-bio.TO
|
http://creativecommons.org/licenses/by-nc-sa/3.0/
|
It is well established that the mechanical environment influences cell
functions in health and disease. Here, we address how the mechanical
environment influences tumor growth, in particular, the shape of solid tumors.
In an in vitro tumor model, which isolates mechanical interactions between
tumor cells and a hydrogel, we find that tumors grow as ellipsoids, resembling
the same, oft-reported observation of in vivo tumors. Specifically, an oblate
ellipsoidal tumor shape robustly occurs when the tumors grow in hydrogels that
are stiffer than the tumors, but when they grow in more compliant hydrogels
they remain closer to spherical in shape. Using large scale, nonlinear
elasticity computations we show that the oblate ellipsoidal shape minimizes the
elastic free energy of the tumor-hydrogel system. Having eliminated a number of
other candidate explanations, we hypothesize that minimization of the elastic
free energy is the reason for predominance of the experimentally observed
ellipsoidal shape. This result may hold significance for explaining the shape
progression of early solid tumors in vivo and is an important step in
understanding the processes underlying solid tumor growth.
|
[
{
"created": "Tue, 13 May 2014 20:04:14 GMT",
"version": "v1"
}
] |
2015-06-19
|
[
[
"Mills",
"Kristen L.",
""
],
[
"Kemkemer",
"Ralf",
""
],
[
"Rudraraju",
"Shiva",
""
],
[
"Garikipati",
"Krishna",
""
]
] |
It is well established that the mechanical environment influences cell functions in health and disease. Here, we address how the mechanical environment influences tumor growth, in particular, the shape of solid tumors. In an in vitro tumor model, which isolates mechanical interactions between tumor cells and a hydrogel, we find that tumors grow as ellipsoids, resembling the same, oft-reported observation of in vivo tumors. Specifically, an oblate ellipsoidal tumor shape robustly occurs when the tumors grow in hydrogels that are stiffer than the tumors, but when they grow in more compliant hydrogels they remain closer to spherical in shape. Using large scale, nonlinear elasticity computations we show that the oblate ellipsoidal shape minimizes the elastic free energy of the tumor-hydrogel system. Having eliminated a number of other candidate explanations, we hypothesize that minimization of the elastic free energy is the reason for predominance of the experimentally observed ellipsoidal shape. This result may hold significance for explaining the shape progression of early solid tumors in vivo and is an important step in understanding the processes underlying solid tumor growth.
|
1803.02630
|
Emese Drozsdik
|
Emese J. Drozsdik and Bal\'azs G. Madas
|
Quantitative analysis of the potential role of basal cell hyperplasia in
the relationship between clonal expansion and radon concentration
|
paper presented in the 17th International Symposium on Microdosimetry
(MICROS 2017 - Venice, Italy, 5-10 November, 2017), 5 pages, 1 table, 6
figures
| null | null | null |
q-bio.TO physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Applying the two-stage clonal expansion model to epidemiology of lung cancer
among uranium miners, it has been revealed that radon acts as a promoting agent
facilitating the clonal expansion of already mutated cells. Clonal expansion
rate increases non-linearly by radon concentration showing a plateau above a
given exposure rate. The underlying mechanisms remain unclear. Earlier we
proposed that progenitor cell hyperplasia may be induced upon chronic radon
exposure. The objective of the present study is to test whether the induction
of hyperplasia may provide a quantitative explanation for the plateau in clonal
expansion rate. For this purpose, numerical epithelium models were prepared
with different number of basal cells. Cell nucleus hits were computed by an
own-developed Monte-Carlo code. Surviving fractions were estimated based on the
number of cell nucleus hits. Cell division rate was computed supposing
equilibrium between cell death and cell division. It was also supposed that
clonal expansion rate is proportional to cell division rate, and therefore the
relative increase in cell division rate and clonal expansion rate are the same
functions of exposure rate. While the simulation results highly depend on model
parameters with high uncertainty, a parameter set has been found resulting in a
cell division rate exposure rate relationship corresponding to the plateau in
clonal expansion rate. Due to the high uncertainty of the applied parameters,
however, further studies are required to decide whether the induction of
hyperplasia is responsible for the non-linear increase in clonal expansion rate
or not. Nevertheless the present study exemplifies how computational modelling
can contribute to the integration of observational and experimental radiation
protection research.
|
[
{
"created": "Wed, 7 Mar 2018 13:02:12 GMT",
"version": "v1"
}
] |
2018-03-08
|
[
[
"Drozsdik",
"Emese J.",
""
],
[
"Madas",
"Balázs G.",
""
]
] |
Applying the two-stage clonal expansion model to epidemiology of lung cancer among uranium miners, it has been revealed that radon acts as a promoting agent facilitating the clonal expansion of already mutated cells. Clonal expansion rate increases non-linearly by radon concentration showing a plateau above a given exposure rate. The underlying mechanisms remain unclear. Earlier we proposed that progenitor cell hyperplasia may be induced upon chronic radon exposure. The objective of the present study is to test whether the induction of hyperplasia may provide a quantitative explanation for the plateau in clonal expansion rate. For this purpose, numerical epithelium models were prepared with different number of basal cells. Cell nucleus hits were computed by an own-developed Monte-Carlo code. Surviving fractions were estimated based on the number of cell nucleus hits. Cell division rate was computed supposing equilibrium between cell death and cell division. It was also supposed that clonal expansion rate is proportional to cell division rate, and therefore the relative increase in cell division rate and clonal expansion rate are the same functions of exposure rate. While the simulation results highly depend on model parameters with high uncertainty, a parameter set has been found resulting in a cell division rate exposure rate relationship corresponding to the plateau in clonal expansion rate. Due to the high uncertainty of the applied parameters, however, further studies are required to decide whether the induction of hyperplasia is responsible for the non-linear increase in clonal expansion rate or not. Nevertheless the present study exemplifies how computational modelling can contribute to the integration of observational and experimental radiation protection research.
|
q-bio/0506010
|
Ciro Minichini
|
C. Minichini and A. Sciarrino
|
Mutation model for nucleotide sequences based on crystal basis
|
27 pages, 9 figures
| null | null |
DSF 14/2005
|
q-bio.BM q-bio.OT
| null |
A nucleotides sequence is identified, in the two (four) letters alphabet, by
the the labels of a vector state of an irreducible representation of U_q(sl(2))
(U_q(sl(2) + sl(2))), in the limit q -> 0. A master equation for the
distribution function is written, where the intensity of the one-spin flip is
assumed to depend from the variation of the labels of the state. In the two
letters approximation, the numerically computed equilibrium distribution for
short sequences is nicely fitted by a Yule distribution, which is the observed
distribution of the ranked short oligonucleotides frequency in DNA. The four
letter alphabet description, applied to the codons, is able to reproduce the
form of the fitted rank ordered usage frequencies distribution.
|
[
{
"created": "Wed, 8 Jun 2005 15:25:40 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Minichini",
"C.",
""
],
[
"Sciarrino",
"A.",
""
]
] |
A nucleotides sequence is identified, in the two (four) letters alphabet, by the the labels of a vector state of an irreducible representation of U_q(sl(2)) (U_q(sl(2) + sl(2))), in the limit q -> 0. A master equation for the distribution function is written, where the intensity of the one-spin flip is assumed to depend from the variation of the labels of the state. In the two letters approximation, the numerically computed equilibrium distribution for short sequences is nicely fitted by a Yule distribution, which is the observed distribution of the ranked short oligonucleotides frequency in DNA. The four letter alphabet description, applied to the codons, is able to reproduce the form of the fitted rank ordered usage frequencies distribution.
|
1504.07523
|
Luca Salasnich
|
Luca Salasnich
|
Power spectrum and diffusion of the Amari neural field
|
8 pages, 2 figures, improved version with inclusion of
reaction-diffusion equation and dual neural field. To be published in the
open access journal Symmetry
|
Symmetry 11, 134 (2019)
|
10.3390/sym11020134
| null |
q-bio.NC nlin.PS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We study the power spectrum of a space-time dependent neural field which
describes the average membrane potential of neurons in a single layer. This
neural field is modelled by a dissipative integro-differential equation, the
so-called Amari equation. By considering a small perturbation with respect to a
stationary and uniform configuration of the neural field we derive a linearized
equation which is solved for a generic external stimulus by using the Fourier
transform into wavevector-freqency domain, finding an analytical formula for
the power spectrum of the neural field. In addition, after proving that for
large wavelengths the linearized Amari equation is equivalent to a diffusion
equation which admits space-time dependent analytical solutions, we take into
account the nonlinearity of the Amari equation. We find that for large
wavelengths a weak nonlinearity in the Amari equation gives rise to a
reaction-diffusion equation which can be formally derived from a neural action
functional by introducing a dual neural field. For some initial conditions, we
discuss analytical solutions of this reaction-diffusion equation.
|
[
{
"created": "Tue, 28 Apr 2015 15:11:40 GMT",
"version": "v1"
},
{
"created": "Thu, 30 Jul 2015 10:21:56 GMT",
"version": "v2"
},
{
"created": "Mon, 31 Aug 2015 12:46:11 GMT",
"version": "v3"
},
{
"created": "Thu, 27 Jul 2017 15:28:41 GMT",
"version": "v4"
},
{
"created": "Mon, 31 Jul 2017 10:21:25 GMT",
"version": "v5"
},
{
"created": "Thu, 24 Jan 2019 17:21:06 GMT",
"version": "v6"
}
] |
2019-01-29
|
[
[
"Salasnich",
"Luca",
""
]
] |
We study the power spectrum of a space-time dependent neural field which describes the average membrane potential of neurons in a single layer. This neural field is modelled by a dissipative integro-differential equation, the so-called Amari equation. By considering a small perturbation with respect to a stationary and uniform configuration of the neural field we derive a linearized equation which is solved for a generic external stimulus by using the Fourier transform into wavevector-freqency domain, finding an analytical formula for the power spectrum of the neural field. In addition, after proving that for large wavelengths the linearized Amari equation is equivalent to a diffusion equation which admits space-time dependent analytical solutions, we take into account the nonlinearity of the Amari equation. We find that for large wavelengths a weak nonlinearity in the Amari equation gives rise to a reaction-diffusion equation which can be formally derived from a neural action functional by introducing a dual neural field. For some initial conditions, we discuss analytical solutions of this reaction-diffusion equation.
|
2306.15379
|
Matthew Simpson
|
Matthew J Simpson, Nizhum Rahman, Scott W McCue, Alexander KY Tam
|
Survival, extinction, and interface stability in a two--phase moving
boundary model of biological invasion
|
36 pages. 10 figures
| null | null | null |
q-bio.PE math.AP nlin.PS physics.bio-ph
|
http://creativecommons.org/licenses/by/4.0/
|
We consider a moving boundary mathematical model of biological invasion. The
model describes the spatiotemporal evolution of two adjacent populations: each
population undergoes linear diffusion and logistic growth, and the boundary
between the two populations evolves according to a two--phase Stefan condition.
This mathematical model describes situations where one population invades into
regions occupied by the other population, such as the spreading of a malignant
tumour into surrounding tissues. Full time--dependent numerical solutions are
obtained using a level--set numerical method. We use these numerical solutions
to explore several properties of the model including: (i) survival and
extinction of one population initially surrounded by the other; and (ii) linear
stability of the moving front boundary in the context of a travelling wave
solution subjected to transverse perturbations. Overall, we show that many
features of the well--studied one--phase single population analogue of this
model can be very different in the more realistic two--phase setting. These
results are important because realistic examples of biological invasion involve
interactions between multiple populations and so great care should be taken
when extrapolating predictions from a one--phase single population model to
cases for which multiple populations are present. Open source Julia--based
software is available on GitHub to replicate all results in this study.
|
[
{
"created": "Tue, 27 Jun 2023 10:58:31 GMT",
"version": "v1"
},
{
"created": "Thu, 6 Jul 2023 07:21:35 GMT",
"version": "v2"
},
{
"created": "Fri, 1 Sep 2023 23:32:27 GMT",
"version": "v3"
}
] |
2023-09-06
|
[
[
"Simpson",
"Matthew J",
""
],
[
"Rahman",
"Nizhum",
""
],
[
"McCue",
"Scott W",
""
],
[
"Tam",
"Alexander KY",
""
]
] |
We consider a moving boundary mathematical model of biological invasion. The model describes the spatiotemporal evolution of two adjacent populations: each population undergoes linear diffusion and logistic growth, and the boundary between the two populations evolves according to a two--phase Stefan condition. This mathematical model describes situations where one population invades into regions occupied by the other population, such as the spreading of a malignant tumour into surrounding tissues. Full time--dependent numerical solutions are obtained using a level--set numerical method. We use these numerical solutions to explore several properties of the model including: (i) survival and extinction of one population initially surrounded by the other; and (ii) linear stability of the moving front boundary in the context of a travelling wave solution subjected to transverse perturbations. Overall, we show that many features of the well--studied one--phase single population analogue of this model can be very different in the more realistic two--phase setting. These results are important because realistic examples of biological invasion involve interactions between multiple populations and so great care should be taken when extrapolating predictions from a one--phase single population model to cases for which multiple populations are present. Open source Julia--based software is available on GitHub to replicate all results in this study.
|
1511.05227
|
Marisa Eisenberg
|
Olivia J. Walch, Marisa C. Eisenberg
|
Parameter identifiability and identifiable combinations in generalized
Hodgkin-Huxley models
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The use of Hodgkin-Huxley (HH) equations abounds in the literature, but the
identifiability of the HH model parameters has not been broadly considered.
Identifiability analysis addresses the question of whether it is possible to
estimate the model parameters for a given choice of measurement data and
experimental inputs. Here we explore the structural identifiability properties
of a generalized form of HH from voltage clamp data. Through a scaling
argument, we conclude that the steady-state gating variables are not
identifiable from voltage clamp data, and then further show that their product
together with the conductance term forms an identifiable combination. We
additionally show that these parameters become identifiable when the initial
conditions for each of the gating variables are known. The time constants for
each gating variable are shown to be identifiable, and a novel method for
estimating them is presented. Finally, the exponents of the gating variables
are shown to be identifiable in the two-gate case, and we conjecture these to
be identifiable in the general case. These results are broadly applicable to
models using HH-like formalisms, and show in general which parameters and
combinations of parameters are possible to estimate from voltage clamp data.
|
[
{
"created": "Mon, 16 Nov 2015 23:58:18 GMT",
"version": "v1"
}
] |
2015-11-18
|
[
[
"Walch",
"Olivia J.",
""
],
[
"Eisenberg",
"Marisa C.",
""
]
] |
The use of Hodgkin-Huxley (HH) equations abounds in the literature, but the identifiability of the HH model parameters has not been broadly considered. Identifiability analysis addresses the question of whether it is possible to estimate the model parameters for a given choice of measurement data and experimental inputs. Here we explore the structural identifiability properties of a generalized form of HH from voltage clamp data. Through a scaling argument, we conclude that the steady-state gating variables are not identifiable from voltage clamp data, and then further show that their product together with the conductance term forms an identifiable combination. We additionally show that these parameters become identifiable when the initial conditions for each of the gating variables are known. The time constants for each gating variable are shown to be identifiable, and a novel method for estimating them is presented. Finally, the exponents of the gating variables are shown to be identifiable in the two-gate case, and we conjecture these to be identifiable in the general case. These results are broadly applicable to models using HH-like formalisms, and show in general which parameters and combinations of parameters are possible to estimate from voltage clamp data.
|
2009.12413
|
Katherine St. John
|
Nathan Davidov, Amanda Hernandez, Justin Jian, Patrick McKenna, K.A.
Medlin, Roadra Mojumder, Megan Owen, Andrew Quijano, Amanda Rodriguez,
Katherine St. John, Katherine Thai, Meliza Uraga
|
Maximum Covering Subtrees for Phylogenetic Networks
| null | null |
10.1109/TCBB.2020.3040910
| null |
q-bio.PE cs.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Tree-based phylogenetic networks, which may be roughly defined as
leaf-labeled networks built by adding arcs only between the original tree
edges, have elegant properties for modeling evolutionary histories. We answer
an open question of Francis, Semple, and Steel about the complexity of
determining how far a phylogenetic network is from being tree-based, including
non-binary phylogenetic networks. We show that finding a phylogenetic tree
covering the maximum number of nodes in a phylogenetic network can be be
computed in polynomial time via an encoding into a minimum-cost maximum flow
problem.
|
[
{
"created": "Fri, 25 Sep 2020 19:47:36 GMT",
"version": "v1"
},
{
"created": "Tue, 24 Nov 2020 16:59:04 GMT",
"version": "v2"
}
] |
2022-10-26
|
[
[
"Davidov",
"Nathan",
""
],
[
"Hernandez",
"Amanda",
""
],
[
"Jian",
"Justin",
""
],
[
"McKenna",
"Patrick",
""
],
[
"Medlin",
"K. A.",
""
],
[
"Mojumder",
"Roadra",
""
],
[
"Owen",
"Megan",
""
],
[
"Quijano",
"Andrew",
""
],
[
"Rodriguez",
"Amanda",
""
],
[
"John",
"Katherine St.",
""
],
[
"Thai",
"Katherine",
""
],
[
"Uraga",
"Meliza",
""
]
] |
Tree-based phylogenetic networks, which may be roughly defined as leaf-labeled networks built by adding arcs only between the original tree edges, have elegant properties for modeling evolutionary histories. We answer an open question of Francis, Semple, and Steel about the complexity of determining how far a phylogenetic network is from being tree-based, including non-binary phylogenetic networks. We show that finding a phylogenetic tree covering the maximum number of nodes in a phylogenetic network can be be computed in polynomial time via an encoding into a minimum-cost maximum flow problem.
|
2308.05122
|
Nicha Dvornek
|
Nicha C. Dvornek, Catherine Sullivan, James S. Duncan, Abha R. Gupta
|
Copy Number Variation Informs fMRI-based Prediction of Autism Spectrum
Disorder
|
Accepted by Machine Learning in Clinical Neuroimaging 2023 (MICCAI
workshop), preprint version
| null | null | null |
q-bio.QM cs.CV cs.LG eess.IV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The multifactorial etiology of autism spectrum disorder (ASD) suggests that
its study would benefit greatly from multimodal approaches that combine data
from widely varying platforms, e.g., neuroimaging, genetics, and clinical
characterization. Prior neuroimaging-genetic analyses often apply naive feature
concatenation approaches in data-driven work or use the findings from one
modality to guide posthoc analysis of another, missing the opportunity to
analyze the paired multimodal data in a truly unified approach. In this paper,
we develop a more integrative model for combining genetic, demographic, and
neuroimaging data. Inspired by the influence of genotype on phenotype, we
propose using an attention-based approach where the genetic data guides
attention to neuroimaging features of importance for model prediction. The
genetic data is derived from copy number variation parameters, while the
neuroimaging data is from functional magnetic resonance imaging. We evaluate
the proposed approach on ASD classification and severity prediction tasks,
using a sex-balanced dataset of 228 ASD and typically developing subjects in a
10-fold cross-validation framework. We demonstrate that our attention-based
model combining genetic information, demographic data, and functional magnetic
resonance imaging results in superior prediction performance compared to other
multimodal approaches.
|
[
{
"created": "Tue, 8 Aug 2023 19:53:43 GMT",
"version": "v1"
}
] |
2023-08-11
|
[
[
"Dvornek",
"Nicha C.",
""
],
[
"Sullivan",
"Catherine",
""
],
[
"Duncan",
"James S.",
""
],
[
"Gupta",
"Abha R.",
""
]
] |
The multifactorial etiology of autism spectrum disorder (ASD) suggests that its study would benefit greatly from multimodal approaches that combine data from widely varying platforms, e.g., neuroimaging, genetics, and clinical characterization. Prior neuroimaging-genetic analyses often apply naive feature concatenation approaches in data-driven work or use the findings from one modality to guide posthoc analysis of another, missing the opportunity to analyze the paired multimodal data in a truly unified approach. In this paper, we develop a more integrative model for combining genetic, demographic, and neuroimaging data. Inspired by the influence of genotype on phenotype, we propose using an attention-based approach where the genetic data guides attention to neuroimaging features of importance for model prediction. The genetic data is derived from copy number variation parameters, while the neuroimaging data is from functional magnetic resonance imaging. We evaluate the proposed approach on ASD classification and severity prediction tasks, using a sex-balanced dataset of 228 ASD and typically developing subjects in a 10-fold cross-validation framework. We demonstrate that our attention-based model combining genetic information, demographic data, and functional magnetic resonance imaging results in superior prediction performance compared to other multimodal approaches.
|
0912.4714
|
Emmanuel Tannenbaum
|
Eran Itan and Emmanuel Tannenbaum
|
Semiconservative quasispecies equations for polysomic genomes: The
general case
|
16 pages, 3 figures
| null |
10.1103/PhysRevE.81.061915
| null |
q-bio.PE q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This paper develops a formulation of the quasispecies equations appropriate
for polysomic, semiconservatively replicating genomes. This paper is an
extension of previous work on the subject, which considered the case of haploid
genomes. Here, we develop a more general formulation of the quasispecies
equations that is applicable to diploid and even polyploid genomes.
Interestingly, with an appropriate classification of population fractions, we
obtain a system of equations that is formally identical to the haploid case. As
with the work for haploid genomes, we consider both random and immortal DNA
strand chromosome segregation mechanisms. However, in contrast to the haploid
case, we have found that an analytical solution for the mean fitness is
considerably more difficult to obtain for the polyploid case. Accordingly,
whereas for the haploid case we obtained expressions for the mean fitness for
the case of an analogue of the single-fitness-peak landscape for arbitrary
lesion repair probabilities (thereby allowing for non-complementary genomes),
here we solve for the mean fitness for the restricted case of perfect lesion
repair.
|
[
{
"created": "Wed, 23 Dec 2009 19:13:10 GMT",
"version": "v1"
}
] |
2015-05-14
|
[
[
"Itan",
"Eran",
""
],
[
"Tannenbaum",
"Emmanuel",
""
]
] |
This paper develops a formulation of the quasispecies equations appropriate for polysomic, semiconservatively replicating genomes. This paper is an extension of previous work on the subject, which considered the case of haploid genomes. Here, we develop a more general formulation of the quasispecies equations that is applicable to diploid and even polyploid genomes. Interestingly, with an appropriate classification of population fractions, we obtain a system of equations that is formally identical to the haploid case. As with the work for haploid genomes, we consider both random and immortal DNA strand chromosome segregation mechanisms. However, in contrast to the haploid case, we have found that an analytical solution for the mean fitness is considerably more difficult to obtain for the polyploid case. Accordingly, whereas for the haploid case we obtained expressions for the mean fitness for the case of an analogue of the single-fitness-peak landscape for arbitrary lesion repair probabilities (thereby allowing for non-complementary genomes), here we solve for the mean fitness for the restricted case of perfect lesion repair.
|
2211.09096
|
Thibault Niederhauser
|
Thibault Niederhauser, Adam Lester, Nina Miolane, Khanh Dao Duc, Manu
S. Madhav
|
Testing geometric representation hypotheses from simulated place cell
recordings
|
NeurIPS 2022: NeurReps workshop, extended abstract track
| null | null | null |
q-bio.NC cs.AI cs.LG q-bio.QM
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Hippocampal place cells can encode spatial locations of an animal in physical
or task-relevant spaces. We simulated place cell populations that encoded
either Euclidean- or graph-based positions of a rat navigating to goal nodes in
a maze with a graph topology, and used manifold learning methods such as UMAP
and Autoencoders (AE) to analyze these neural population activities. The
structure of the latent spaces learned by the AE reflects their true geometric
structure, while PCA fails to do so and UMAP is less robust to noise. Our
results support future applications of AE architectures to decipher the
geometry of spatial encoding in the brain.
|
[
{
"created": "Wed, 16 Nov 2022 18:29:17 GMT",
"version": "v1"
}
] |
2022-11-17
|
[
[
"Niederhauser",
"Thibault",
""
],
[
"Lester",
"Adam",
""
],
[
"Miolane",
"Nina",
""
],
[
"Duc",
"Khanh Dao",
""
],
[
"Madhav",
"Manu S.",
""
]
] |
Hippocampal place cells can encode spatial locations of an animal in physical or task-relevant spaces. We simulated place cell populations that encoded either Euclidean- or graph-based positions of a rat navigating to goal nodes in a maze with a graph topology, and used manifold learning methods such as UMAP and Autoencoders (AE) to analyze these neural population activities. The structure of the latent spaces learned by the AE reflects their true geometric structure, while PCA fails to do so and UMAP is less robust to noise. Our results support future applications of AE architectures to decipher the geometry of spatial encoding in the brain.
|
q-bio/0610053
|
Mauricio Barahona
|
Elias August, Kim H. Parker and Mauricio Barahona
|
A Dynamical Model of Lipoprotein Metabolism
|
To appear in Bulletin of Mathematical Biology
| null | null | null |
q-bio.QM q-bio.CB
| null |
We present a dynamical model of lipoprotein metabolism derived by combining a
cascading process in the blood stream and cellular level regulatory dynamics.
We analyse the existence and stability of equilibria and show that this
low-dimensional, nonlinear model exhibits bistability between a low and a high
cholesterol state. A sensitivity analysis indicates that the intracellular
concentration of cholesterol is robust to parametric variations while the
plasma cholesterol can vary widely. We show how the dynamical response to
time-dependent inputs can be used to diagnose the state of the system. We also
establish the connection between parameters in the system and medical and
genetic conditions.
|
[
{
"created": "Sat, 28 Oct 2006 18:30:36 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"August",
"Elias",
""
],
[
"Parker",
"Kim H.",
""
],
[
"Barahona",
"Mauricio",
""
]
] |
We present a dynamical model of lipoprotein metabolism derived by combining a cascading process in the blood stream and cellular level regulatory dynamics. We analyse the existence and stability of equilibria and show that this low-dimensional, nonlinear model exhibits bistability between a low and a high cholesterol state. A sensitivity analysis indicates that the intracellular concentration of cholesterol is robust to parametric variations while the plasma cholesterol can vary widely. We show how the dynamical response to time-dependent inputs can be used to diagnose the state of the system. We also establish the connection between parameters in the system and medical and genetic conditions.
|
1712.06846
|
Tom\'as Revilla
|
Tom\'as A. Revilla and Vlastimil K\v{r}ivan
|
Competition, trait-mediated facilitation, and the structure of
plant-pollinator communities
|
ideal free distribution, isolegs, pollination services, plant
resources, critical transition
|
Journal of Theoretical Biology. Vol. 440, pp. 42-57 (2018)
|
10.1016/j.jtbi.2017.12.019
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In plant-pollinator communities many pollinators are potential generalists
and their preferences for certain plants can change quickly in response to
changes in plant and pollinator densities. These changes in preferences affect
coexistence within pollinator guilds as well as within plant guilds. Using a
mathematical model, we study how adaptations of pollinator preferences
influence population dynamics of a two-plant-two-pollinator community
interaction module. Adaptation leads to coexistence between generalist and
specialist pollinators, and produces complex plant population dynamics,
involving alternative stable states and discrete transitions in the plant
community. Pollinator adaptation also leads to plant-plant apparent
facilitation that is mediated by changes in pollinator preferences. We show
that adaptive pollinator behavior reduces niche overlap and leads to
coexistence by specialization on different plants. Thus, this article documents
how adaptive pollinator preferences for plants change the structure and
coexistence of plant-pollinator communities.
|
[
{
"created": "Tue, 19 Dec 2017 10:12:29 GMT",
"version": "v1"
}
] |
2018-01-03
|
[
[
"Revilla",
"Tomás A.",
""
],
[
"Křivan",
"Vlastimil",
""
]
] |
In plant-pollinator communities many pollinators are potential generalists and their preferences for certain plants can change quickly in response to changes in plant and pollinator densities. These changes in preferences affect coexistence within pollinator guilds as well as within plant guilds. Using a mathematical model, we study how adaptations of pollinator preferences influence population dynamics of a two-plant-two-pollinator community interaction module. Adaptation leads to coexistence between generalist and specialist pollinators, and produces complex plant population dynamics, involving alternative stable states and discrete transitions in the plant community. Pollinator adaptation also leads to plant-plant apparent facilitation that is mediated by changes in pollinator preferences. We show that adaptive pollinator behavior reduces niche overlap and leads to coexistence by specialization on different plants. Thus, this article documents how adaptive pollinator preferences for plants change the structure and coexistence of plant-pollinator communities.
|
1312.3447
|
Rub\'en J. Requejo
|
Rub\'en J. Requejo-Mart\'inez
|
Evolutionary game theory and the tower of Babel of cooperation:
Altruism, free-riding, parasitism and the structure of the interactions in a
world with finite resources
|
38 pages
| null | null | null |
q-bio.PE physics.bio-ph physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The study of the evolution of cooperative behaviours --which provide benefits
to others-- and altruism --which provides benefits to others at a cost to
oneself-- has been on the core of the evolutionary game theoretical framework
since its foundation. The fast development of the theory during the last years
has improved our knowledge of the issue, but carried attached a diversification
of concepts which affected communication between scientists. Furthermore, the
main root of conflict in the struggle for life identified by Darwin, the
limited amount of resources present in any ecosystem, which is assumed to keep
a constant population size in most game theoretical studies, has only recently
been taken into account as explicitly influencing the evolutionary process.
This review concerns about both issues, the conceptual diversification during
the last years and the new results of the resource dependent models. In
extenso: After a historical introduction, a review of the most important
concepts is carried out. Then it is shown that pairwise interactions and
additive fitness determine prisoner's dilemmas (PDs) or harmony games, that two
altruists interacting together may determine a PD, and that the interaction
environment of the most cooperative and less selfish individual in any
population is always a PD. After that, it is shown that in addition to
altruists versus free-riders, the combination of free-riders and parasites
determines a fundamentally different PD. Computer simulations are then carried
out to show that random exploration of parasitism, free-riding and altruism
enables coexistence of the three strategies without the need of reciprocating,
punishing or rewarding strategies. To finish, the problem of the limitation of
resources is reviewed, showing that...
|
[
{
"created": "Thu, 12 Dec 2013 11:14:40 GMT",
"version": "v1"
}
] |
2013-12-13
|
[
[
"Requejo-Martínez",
"Rubén J.",
""
]
] |
The study of the evolution of cooperative behaviours --which provide benefits to others-- and altruism --which provides benefits to others at a cost to oneself-- has been on the core of the evolutionary game theoretical framework since its foundation. The fast development of the theory during the last years has improved our knowledge of the issue, but carried attached a diversification of concepts which affected communication between scientists. Furthermore, the main root of conflict in the struggle for life identified by Darwin, the limited amount of resources present in any ecosystem, which is assumed to keep a constant population size in most game theoretical studies, has only recently been taken into account as explicitly influencing the evolutionary process. This review concerns about both issues, the conceptual diversification during the last years and the new results of the resource dependent models. In extenso: After a historical introduction, a review of the most important concepts is carried out. Then it is shown that pairwise interactions and additive fitness determine prisoner's dilemmas (PDs) or harmony games, that two altruists interacting together may determine a PD, and that the interaction environment of the most cooperative and less selfish individual in any population is always a PD. After that, it is shown that in addition to altruists versus free-riders, the combination of free-riders and parasites determines a fundamentally different PD. Computer simulations are then carried out to show that random exploration of parasitism, free-riding and altruism enables coexistence of the three strategies without the need of reciprocating, punishing or rewarding strategies. To finish, the problem of the limitation of resources is reviewed, showing that...
|
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