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1912.01380
Giulia Marciani
Giulia Marciani, Annamaria Ronchitelli, Simona Arrighi, Federica Badino, Eugenio Bortolini, Paolo Boscato, Francesco Boschin, Jacopo Crezzini, Davide Delpiano, Armando Falcucci, Carla Figus, Federico Lugli, Gregorio Oxilia, Matteo Romandini, Julien Riel-Salvatore, Fabio Negrino, Marco Peresani, Enza Elena Spinapolice, Adriana Moroni, Stefano Benazzi
Lithic techno-complexes in Italy from 50 to 39 thousand years BP: an overview of lithic technological changes across the Middle-Upper Palaeolithic boundary
null
null
10.1016/j.quaint.2019.11.005
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Defining the processes involved in the technical/cultural shifts from the Late Middle to the Early Upper Palaeolithic in Europe (~50-39 thousand years BP) is one of the most important tasks facing prehistoric studies. In this debate Italy plays a pivotal role, due to its geographical position between eastern and western Mediterranean Europe as well as to it being the location of several sites showing Late Mousterian, Uluzzian and Protoaurignacian evidence distributed across the Peninsula. Our study aims to provide a synthesis of the available lithic evidence from this key area through a review of the evidence collected from a number of reference sites. The main technical features of the Late Mousterian, the Uluzzian and the Protoaurignacian traditions are examined from a diachronic and spatial perspective. Our overview allows the identification of major differences in the technological behaviour of these populations, making it possible to propose a number of specific working hypotheses on the basis of which further studies can be carried out. This study presents a detailed comparative study of the whole corpus of the lithic production strategies documented during this interval, and crucial element thus emerge.These data are of primary importance in order to assess the nature of the "transition" phenomenon in Italy, thus contributing to the larger debate about the disappearance of Neandertals and the arrival of early Modern Humans in Europe.
[ { "created": "Tue, 3 Dec 2019 14:11:35 GMT", "version": "v1" }, { "created": "Mon, 16 Dec 2019 16:38:00 GMT", "version": "v2" } ]
2019-12-17
[ [ "Marciani", "Giulia", "" ], [ "Ronchitelli", "Annamaria", "" ], [ "Arrighi", "Simona", "" ], [ "Badino", "Federica", "" ], [ "Bortolini", "Eugenio", "" ], [ "Boscato", "Paolo", "" ], [ "Boschin", "Francesco", "" ], [ "Crezzini", "Jacopo", "" ], [ "Delpiano", "Davide", "" ], [ "Falcucci", "Armando", "" ], [ "Figus", "Carla", "" ], [ "Lugli", "Federico", "" ], [ "Oxilia", "Gregorio", "" ], [ "Romandini", "Matteo", "" ], [ "Riel-Salvatore", "Julien", "" ], [ "Negrino", "Fabio", "" ], [ "Peresani", "Marco", "" ], [ "Spinapolice", "Enza Elena", "" ], [ "Moroni", "Adriana", "" ], [ "Benazzi", "Stefano", "" ] ]
Defining the processes involved in the technical/cultural shifts from the Late Middle to the Early Upper Palaeolithic in Europe (~50-39 thousand years BP) is one of the most important tasks facing prehistoric studies. In this debate Italy plays a pivotal role, due to its geographical position between eastern and western Mediterranean Europe as well as to it being the location of several sites showing Late Mousterian, Uluzzian and Protoaurignacian evidence distributed across the Peninsula. Our study aims to provide a synthesis of the available lithic evidence from this key area through a review of the evidence collected from a number of reference sites. The main technical features of the Late Mousterian, the Uluzzian and the Protoaurignacian traditions are examined from a diachronic and spatial perspective. Our overview allows the identification of major differences in the technological behaviour of these populations, making it possible to propose a number of specific working hypotheses on the basis of which further studies can be carried out. This study presents a detailed comparative study of the whole corpus of the lithic production strategies documented during this interval, and crucial element thus emerge.These data are of primary importance in order to assess the nature of the "transition" phenomenon in Italy, thus contributing to the larger debate about the disappearance of Neandertals and the arrival of early Modern Humans in Europe.
2003.12032
Tom Chou
Lucas B\"ottcher, Mingtao Xia, and Tom Chou
Why case fatality ratios can be misleading: individual- and population-based mortality estimates and factors influencing them
17 pp, 6 figures + Supplementary Information
Physical Biology 17(6), 2020
10.1088/1478-3975/ab9e59
null
q-bio.PE
http://creativecommons.org/licenses/by-nc-sa/4.0/
Different ways of calculating mortality ratios during epidemics have yielded very different results, particularly during the current COVID-19 pandemic. We formulate both a survival probability model and an associated infection duration-dependent SIR model to define individual- and population-based estimates of dynamic mortality ratios. The key parameters that affect the dynamics of the different mortality estimates are the incubation period and the time individuals were infected before confirmation of infection. We stress that none of these ratios are accurately represented by the often misinterpreted case fatality ratio (CFR), the number of deaths to date divided by the total number of confirmed infected cases to date. Using data on the recent SARS-CoV-2 outbreaks, we estimate and compare the different dynamic mortality ratios and highlight their differences. Informed by our modeling, we propose more systematic methods to determine mortality ratios during epidemic outbreaks and discuss sensitivity to confounding effects and uncertainties in the data.
[ { "created": "Thu, 26 Mar 2020 16:54:46 GMT", "version": "v1" }, { "created": "Thu, 2 Apr 2020 09:06:29 GMT", "version": "v2" }, { "created": "Fri, 3 Apr 2020 01:47:33 GMT", "version": "v3" } ]
2020-10-06
[ [ "Böttcher", "Lucas", "" ], [ "Xia", "Mingtao", "" ], [ "Chou", "Tom", "" ] ]
Different ways of calculating mortality ratios during epidemics have yielded very different results, particularly during the current COVID-19 pandemic. We formulate both a survival probability model and an associated infection duration-dependent SIR model to define individual- and population-based estimates of dynamic mortality ratios. The key parameters that affect the dynamics of the different mortality estimates are the incubation period and the time individuals were infected before confirmation of infection. We stress that none of these ratios are accurately represented by the often misinterpreted case fatality ratio (CFR), the number of deaths to date divided by the total number of confirmed infected cases to date. Using data on the recent SARS-CoV-2 outbreaks, we estimate and compare the different dynamic mortality ratios and highlight their differences. Informed by our modeling, we propose more systematic methods to determine mortality ratios during epidemic outbreaks and discuss sensitivity to confounding effects and uncertainties in the data.
1904.00353
Sadegh Movahed
Marjan Mozaffarilegha and S. M. S. Movahed
Long-range temporal correlation in Auditory Brainstem Responses to Spoken Syllable /da/
27 pages, 8 figures and one table
Scientific Reports, volume 9, Article number: 1751 (2019)
10.1038/s41598-018-38215-w
null
q-bio.QM physics.bio-ph q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The speech auditory brainstem response (sABR) is an objective clinical tool to diagnose particular impairments along the auditory brainstem pathways. We explore the scaling behavior of the brainstem in response to synthetic /da/ stimuli using a proposed pipeline including Multifractal Detrended Moving Average Analysis (MFDMA) modified by Singular Value Decomposition. The scaling exponent confirms that all normal sABR are classified into the non-stationary process. The average Hurst exponent is $H=0.77\pm0.12$ at 68\% confidence interval indicating long-range correlation which shows the first universality behavior of sABR. Our findings exhibit that fluctuations in the sABR series are dictated by a mechanism associated with long-term memory of the dynamic of the auditory system in the brainstem level. The $q-$dependency of $h(q)$ demonstrates that underlying data sets have multifractal nature revealing the second universality behavior of the normal sABR samples. Comparing Hurst exponent of original sABR with the results of the corresponding shuffled and surrogate series, we conclude that its multifractality is almost due to the long-range temporal correlations which are devoted to the third universality. Finally, the presence of long-range correlation which is related to the slow timescales in the subcortical level and integration of information in the brainstem network is confirmed.
[ { "created": "Sun, 31 Mar 2019 07:36:56 GMT", "version": "v1" } ]
2019-04-02
[ [ "Mozaffarilegha", "Marjan", "" ], [ "Movahed", "S. M. S.", "" ] ]
The speech auditory brainstem response (sABR) is an objective clinical tool to diagnose particular impairments along the auditory brainstem pathways. We explore the scaling behavior of the brainstem in response to synthetic /da/ stimuli using a proposed pipeline including Multifractal Detrended Moving Average Analysis (MFDMA) modified by Singular Value Decomposition. The scaling exponent confirms that all normal sABR are classified into the non-stationary process. The average Hurst exponent is $H=0.77\pm0.12$ at 68\% confidence interval indicating long-range correlation which shows the first universality behavior of sABR. Our findings exhibit that fluctuations in the sABR series are dictated by a mechanism associated with long-term memory of the dynamic of the auditory system in the brainstem level. The $q-$dependency of $h(q)$ demonstrates that underlying data sets have multifractal nature revealing the second universality behavior of the normal sABR samples. Comparing Hurst exponent of original sABR with the results of the corresponding shuffled and surrogate series, we conclude that its multifractality is almost due to the long-range temporal correlations which are devoted to the third universality. Finally, the presence of long-range correlation which is related to the slow timescales in the subcortical level and integration of information in the brainstem network is confirmed.
0707.1238
V. Moskovkin
M. B. Manuylov, I. I. Mavrov, and V. M. Moskovkin
Infected surfaces of vehicles as possible way of people's infection by bird flu pathogenic culture
8 pages
null
null
null
q-bio.OT
null
Possible variant of people's infection by bird flu pathogenic culture in passing of everyday infection is presented in the work: through the contact of open parts of the skin with infected surfaces of the vehicle, that is the sequent of the reused water, which contains all species spectrum of pathogen accumulated on the urban areas, used in process of washing
[ { "created": "Mon, 9 Jul 2007 12:21:20 GMT", "version": "v1" } ]
2007-07-10
[ [ "Manuylov", "M. B.", "" ], [ "Mavrov", "I. I.", "" ], [ "Moskovkin", "V. M.", "" ] ]
Possible variant of people's infection by bird flu pathogenic culture in passing of everyday infection is presented in the work: through the contact of open parts of the skin with infected surfaces of the vehicle, that is the sequent of the reused water, which contains all species spectrum of pathogen accumulated on the urban areas, used in process of washing
2211.13188
Nicolas Raymond
Nicolas Raymond, Maxime Caru, Hakima Laribi, Mehdi Mitiche, Val\'erie Marcil, Maja Krajinovic, Daniel Curnier, Daniel Sinnett, Martin Valli\`eres
Machine learning strategies to predict late adverse effects in childhood acute lymphoblastic leukemia survivors
Submitted to Communications Medicine
null
null
null
q-bio.QM
http://creativecommons.org/licenses/by/4.0/
Acute lymphoblastic leukemia is the most frequent pediatric cancer. Approximately two third of survivors develop one or more health complications known as late adverse effects following their treatments. The existing measures offered to patients during their follow-up visits to the hospital are rather standardized for all childhood cancer survivors and not necessarily personalized for childhood ALL survivors. As a result, late adverse effects may be underdiagnosed and, in most cases, only taken care of following their appearance. Thus, it is necessary to predict these treatment-related conditions earlier in order to prevent them and enhance the survivors' health. Multiple studies have investigated the development of late adverse effects prediction tools to offer better personalized follow-up methods. However, no solution integrated the usage of neural networks to date. In this work, we developed graph-based parameters-efficient neural networks and promoted their interpretability with multiple post-hoc analyses. We first proposed a new disease-specific VO$_2$ peak prediction model that does not require patients to participate to a physical function test (e.g., 6-minute walk test) and further created an obesity prediction model using clinical variables that are available from the end of childhood ALL treatment as well as genomic variables. Our solutions were able to achieve better performance than linear and tree-based models on small cohorts of patients ($\leq$ 223) for both tasks.
[ { "created": "Wed, 23 Nov 2022 18:10:52 GMT", "version": "v1" }, { "created": "Wed, 30 Nov 2022 19:24:56 GMT", "version": "v2" } ]
2022-12-02
[ [ "Raymond", "Nicolas", "" ], [ "Caru", "Maxime", "" ], [ "Laribi", "Hakima", "" ], [ "Mitiche", "Mehdi", "" ], [ "Marcil", "Valérie", "" ], [ "Krajinovic", "Maja", "" ], [ "Curnier", "Daniel", "" ], [ "Sinnett", "Daniel", "" ], [ "Vallières", "Martin", "" ] ]
Acute lymphoblastic leukemia is the most frequent pediatric cancer. Approximately two third of survivors develop one or more health complications known as late adverse effects following their treatments. The existing measures offered to patients during their follow-up visits to the hospital are rather standardized for all childhood cancer survivors and not necessarily personalized for childhood ALL survivors. As a result, late adverse effects may be underdiagnosed and, in most cases, only taken care of following their appearance. Thus, it is necessary to predict these treatment-related conditions earlier in order to prevent them and enhance the survivors' health. Multiple studies have investigated the development of late adverse effects prediction tools to offer better personalized follow-up methods. However, no solution integrated the usage of neural networks to date. In this work, we developed graph-based parameters-efficient neural networks and promoted their interpretability with multiple post-hoc analyses. We first proposed a new disease-specific VO$_2$ peak prediction model that does not require patients to participate to a physical function test (e.g., 6-minute walk test) and further created an obesity prediction model using clinical variables that are available from the end of childhood ALL treatment as well as genomic variables. Our solutions were able to achieve better performance than linear and tree-based models on small cohorts of patients ($\leq$ 223) for both tasks.
2005.12252
Carlo R. Contaldi
Carlo R. Contaldi
COVID-19: Nowcasting Reproduction Factors Using Biased Case Testing Data
null
null
null
null
q-bio.PE physics.med-ph physics.soc-ph q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Timely estimation of the current value for COVID-19 reproduction factor $R$ has become a key aim of efforts to inform management strategies. $R$ is an important metric used by policy-makers in setting mitigation levels and is also important for accurate modelling of epidemic progression. This brief paper introduces a method for estimating $R$ from biased case testing data. Using testing data, rather than hospitalisation or death data, provides a much earlier metric along the symptomatic progression scale. This can be hugely important when fighting the exponential nature of an epidemic. We develop a practical estimator and apply it to Scottish case testing data to infer a current (20 May 2020) $R$ value of $0.74$ with $95\%$ confidence interval $[0.48 - 0.86]$.
[ { "created": "Mon, 25 May 2020 17:54:13 GMT", "version": "v1" } ]
2020-05-26
[ [ "Contaldi", "Carlo R.", "" ] ]
Timely estimation of the current value for COVID-19 reproduction factor $R$ has become a key aim of efforts to inform management strategies. $R$ is an important metric used by policy-makers in setting mitigation levels and is also important for accurate modelling of epidemic progression. This brief paper introduces a method for estimating $R$ from biased case testing data. Using testing data, rather than hospitalisation or death data, provides a much earlier metric along the symptomatic progression scale. This can be hugely important when fighting the exponential nature of an epidemic. We develop a practical estimator and apply it to Scottish case testing data to infer a current (20 May 2020) $R$ value of $0.74$ with $95\%$ confidence interval $[0.48 - 0.86]$.
2306.15113
Alan Rubin
Melina Claussnitzer, Victoria N. Parikh, Alex H. Wagner, Jeremy A. Arbesfeld, Carol J. Bult, Helen V. Firth, Lara A. Muffley, Alex N. Nguyen Ba, Kevin Riehle, Frederick P. Roth, Daniel Tabet, Benedetta Bolognesi, Andrew M. Glazer, Alan F. Rubin
Minimum information and guidelines for reporting a Multiplexed Assay of Variant Effect
null
null
null
null
q-bio.OT
http://creativecommons.org/licenses/by/4.0/
Multiplexed Assays of Variant Effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines has led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.
[ { "created": "Mon, 26 Jun 2023 23:43:03 GMT", "version": "v1" } ]
2023-06-28
[ [ "Claussnitzer", "Melina", "" ], [ "Parikh", "Victoria N.", "" ], [ "Wagner", "Alex H.", "" ], [ "Arbesfeld", "Jeremy A.", "" ], [ "Bult", "Carol J.", "" ], [ "Firth", "Helen V.", "" ], [ "Muffley", "Lara A.", "" ], [ "Ba", "Alex N. Nguyen", "" ], [ "Riehle", "Kevin", "" ], [ "Roth", "Frederick P.", "" ], [ "Tabet", "Daniel", "" ], [ "Bolognesi", "Benedetta", "" ], [ "Glazer", "Andrew M.", "" ], [ "Rubin", "Alan F.", "" ] ]
Multiplexed Assays of Variant Effect (MAVEs) have emerged as a powerful approach for interrogating thousands of genetic variants in a single experiment. The flexibility and widespread adoption of these techniques across diverse disciplines has led to a heterogeneous mix of data formats and descriptions, which complicates the downstream use of the resulting datasets. To address these issues and promote reproducibility and reuse of MAVE data, we define a set of minimum information standards for MAVE data and metadata and outline a controlled vocabulary aligned with established biomedical ontologies for describing these experimental designs.
1312.0226
Olivier Rivoire
Olivier Rivoire and Stanislas Leibler
A Model for the Generation and Transmission of Variations in Evolution
null
null
10.1073/pnas.1323901111
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The inheritance of characteristics induced by the environment has often been opposed to the theory of evolution by natural selection. Yet, while evolution by natural selection requires new heritable traits to be produced and transmitted, it does not prescribe, per se, the mechanisms by which this is operated. The mechanisms of inheritance are not, however, unconstrained, since they are themselves subject to natural selection. We introduce a general, analytically solvable mathematical model to compare the adaptive value of different schemes of inheritance. Our model allows for variations to be inherited, randomly produced, or environmentally induced, and, irrespectively, to be either transmitted or not during reproduction. The adaptation of the different schemes for processing variations is quantified for a range of fluctuating environments, following an approach that links quantitative genetics with stochastic control theory.
[ { "created": "Sun, 1 Dec 2013 14:15:32 GMT", "version": "v1" } ]
2015-06-18
[ [ "Rivoire", "Olivier", "" ], [ "Leibler", "Stanislas", "" ] ]
The inheritance of characteristics induced by the environment has often been opposed to the theory of evolution by natural selection. Yet, while evolution by natural selection requires new heritable traits to be produced and transmitted, it does not prescribe, per se, the mechanisms by which this is operated. The mechanisms of inheritance are not, however, unconstrained, since they are themselves subject to natural selection. We introduce a general, analytically solvable mathematical model to compare the adaptive value of different schemes of inheritance. Our model allows for variations to be inherited, randomly produced, or environmentally induced, and, irrespectively, to be either transmitted or not during reproduction. The adaptation of the different schemes for processing variations is quantified for a range of fluctuating environments, following an approach that links quantitative genetics with stochastic control theory.
2408.00039
Philip Greulich
Philip Greulich
Cooperative SIR dynamics as a model for spontaneous blood clot initiation
null
null
null
null
q-bio.QM
http://creativecommons.org/licenses/by/4.0/
Blood clotting is an important physiological process to suppress bleeding upon injury, but when it occurs inadvertently, it can cause thrombosis, which can lead to life threatening conditions. Hence, understanding the microscopic mechanistic factors for inadvertent, spontaneous blood clotting, in absence of a vessel breach, can help in predicting and adverting such conditions. Here, we present a minimal model -- reminiscent of the SIR model -- for the initiating stage of spontaneous blood clotting, the collective activation of blood platelets. This model predicts that in the presence of very small initial activation signals, macroscopic activation of the platelet population requires a sufficient degree of heterogeneity of platelet sensitivity. To propagate the activation signal and achieve collective activation of the bulk platelet population, it requires the presence of, possibly only few, hyper-sensitive platelets, but also a sufficient proportion of platelets with intermediate, yet higher-than-average sensitivity. A comparison with experimental results demonstrates a qualitative agreement for high platelet signalling activity.
[ { "created": "Wed, 31 Jul 2024 13:48:51 GMT", "version": "v1" } ]
2024-08-02
[ [ "Greulich", "Philip", "" ] ]
Blood clotting is an important physiological process to suppress bleeding upon injury, but when it occurs inadvertently, it can cause thrombosis, which can lead to life threatening conditions. Hence, understanding the microscopic mechanistic factors for inadvertent, spontaneous blood clotting, in absence of a vessel breach, can help in predicting and adverting such conditions. Here, we present a minimal model -- reminiscent of the SIR model -- for the initiating stage of spontaneous blood clotting, the collective activation of blood platelets. This model predicts that in the presence of very small initial activation signals, macroscopic activation of the platelet population requires a sufficient degree of heterogeneity of platelet sensitivity. To propagate the activation signal and achieve collective activation of the bulk platelet population, it requires the presence of, possibly only few, hyper-sensitive platelets, but also a sufficient proportion of platelets with intermediate, yet higher-than-average sensitivity. A comparison with experimental results demonstrates a qualitative agreement for high platelet signalling activity.
1502.04295
Wilhelm Stannat
Martin Sauer and Wilhelm Stannat
Reliability of signal transmission in stochastic nerve axon equations
9 pages, 7 figures
J Comput Neurosci, vol. 40, pp. 103-111, 2016
10.1007/s10827-015-0586-0
null
q-bio.NC math.DS math.PR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a method for computing probabilities for spontaneous activity and propagation fail- ure of the action potential in spatially extended, conductance-based neuronal models subject to channel noise, based on statistical properties of the membrane potential. We compare different estimators with respect to the quality of detection, computational costs and robustness and propose the integral of the membrane potential along the axon as an appropriate estimator to detect both spontaneous activity and propagation failure. Performing a model reduction we achieve a simplified analytical expression based on the linearization at the resting potential (resp. the traveling action potential). This allows to approximate the probabilities for spontaneous activity and propagation failure in terms of (classical) hitting probabilities of one-dimensional linear stochastic differential equations. The quality of the approximation with respect to the noise amplitude is discussed and illustrated with numerical results for the spatially extended Hodgkin-Huxley.
[ { "created": "Sun, 15 Feb 2015 09:12:03 GMT", "version": "v1" }, { "created": "Mon, 28 Sep 2015 10:21:29 GMT", "version": "v2" }, { "created": "Mon, 21 Mar 2016 07:32:08 GMT", "version": "v3" } ]
2020-01-16
[ [ "Sauer", "Martin", "" ], [ "Stannat", "Wilhelm", "" ] ]
We introduce a method for computing probabilities for spontaneous activity and propagation fail- ure of the action potential in spatially extended, conductance-based neuronal models subject to channel noise, based on statistical properties of the membrane potential. We compare different estimators with respect to the quality of detection, computational costs and robustness and propose the integral of the membrane potential along the axon as an appropriate estimator to detect both spontaneous activity and propagation failure. Performing a model reduction we achieve a simplified analytical expression based on the linearization at the resting potential (resp. the traveling action potential). This allows to approximate the probabilities for spontaneous activity and propagation failure in terms of (classical) hitting probabilities of one-dimensional linear stochastic differential equations. The quality of the approximation with respect to the noise amplitude is discussed and illustrated with numerical results for the spatially extended Hodgkin-Huxley.
1304.5848
James Dowty
James G. Dowty, Graham B. Byrnes and Dorota M. Gertig
The time-evolution of DCIS size distributions with applications to breast cancer growth and progression
12 pages, 2 figures and 1 table. To appear in Mathematical Medicine and Biology
null
10.1093/imammb/dqt014
null
q-bio.PE q-bio.QM q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ductal carcinoma {\em in situ} (DCIS) lesions are non-invasive tumours of the breast which are thought to precede most invasive breast cancers (IBC). As individual DCIS lesions are initiated, grow and invade (i.e. become IBC) the size distribution of the DCIS lesions present in a given human population will evolve. We derive a differential equation governing this evolution and show, for given assumptions about growth and invasion, that there is a unique distribution which does not vary with time. Further, we show that any initial distribution converges to this stationary distribution exponentially quickly. It is therefore reasonable to assume that the stationary distribution is equal to the true DCIS size distribution, at least for human populations which are relatively stable with respect to the determinants of breast cancer. Based on this assumption and the size data of 110 DCIS lesions detected in a mammographic screening program between 1993 and 2000, we produce maximum likelihood estimates for certain growth and invasion parameters. Assuming that DCIS size is proportional to a positive power $p$ of the time since tumour initiation we estimate $p$ to be 0.50 with a 95% confidence interval of $(0.35, 0.71)$. Therefore we estimate that DCIS lesions follow a square-root growth law and hence that they grow rapidly when small and relatively slowly when large. Our approach and results should be useful for other mathematical studies of cancer, especially those investigating biological mechanisms of invasion.
[ { "created": "Mon, 22 Apr 2013 06:15:56 GMT", "version": "v1" }, { "created": "Tue, 25 Jun 2013 05:52:58 GMT", "version": "v2" } ]
2013-12-03
[ [ "Dowty", "James G.", "" ], [ "Byrnes", "Graham B.", "" ], [ "Gertig", "Dorota M.", "" ] ]
Ductal carcinoma {\em in situ} (DCIS) lesions are non-invasive tumours of the breast which are thought to precede most invasive breast cancers (IBC). As individual DCIS lesions are initiated, grow and invade (i.e. become IBC) the size distribution of the DCIS lesions present in a given human population will evolve. We derive a differential equation governing this evolution and show, for given assumptions about growth and invasion, that there is a unique distribution which does not vary with time. Further, we show that any initial distribution converges to this stationary distribution exponentially quickly. It is therefore reasonable to assume that the stationary distribution is equal to the true DCIS size distribution, at least for human populations which are relatively stable with respect to the determinants of breast cancer. Based on this assumption and the size data of 110 DCIS lesions detected in a mammographic screening program between 1993 and 2000, we produce maximum likelihood estimates for certain growth and invasion parameters. Assuming that DCIS size is proportional to a positive power $p$ of the time since tumour initiation we estimate $p$ to be 0.50 with a 95% confidence interval of $(0.35, 0.71)$. Therefore we estimate that DCIS lesions follow a square-root growth law and hence that they grow rapidly when small and relatively slowly when large. Our approach and results should be useful for other mathematical studies of cancer, especially those investigating biological mechanisms of invasion.
1305.3495
Xiao-hua Cao
Xiao-hua Cao, Chao Li, Carl M Gaspar, Bei Jiang
The overlap of neural selectivity between faces and words: evidences from the N170 adaptation effect
null
null
null
null
q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Faces and words both evoke an N170, a strong electrophysiological response that is often used as a marker for the early stages of expert pattern perception. We examine the relationship of neural selectivity between faces and words by using a novel application of cross-category adaptation to the N170. We report a strong asymmetry between N170 adaptation induced by faces and by words. This is the first electrophysiological result showing that neural selectivity to faces encompasses neural selectivity to words, and suggests that the N170 response to faces constitutes a neural marker for versatile representations of familiar visual patterns.
[ { "created": "Wed, 15 May 2013 14:37:05 GMT", "version": "v1" } ]
2013-05-16
[ [ "Cao", "Xiao-hua", "" ], [ "Li", "Chao", "" ], [ "Gaspar", "Carl M", "" ], [ "Jiang", "Bei", "" ] ]
Faces and words both evoke an N170, a strong electrophysiological response that is often used as a marker for the early stages of expert pattern perception. We examine the relationship of neural selectivity between faces and words by using a novel application of cross-category adaptation to the N170. We report a strong asymmetry between N170 adaptation induced by faces and by words. This is the first electrophysiological result showing that neural selectivity to faces encompasses neural selectivity to words, and suggests that the N170 response to faces constitutes a neural marker for versatile representations of familiar visual patterns.
0902.4021
Michael Deem
Jiankui He, Jun Sun, and Michael W. Deem
Spontaneous Emergence of Modularity in a Model of Evolving Individuals and in Real Networks
27 pages, 24 figures; to appear in Phys. Rev. E
null
10.1103/PhysRevE.79.031907
null
q-bio.MN q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the selective forces that promote the emergence of modularity in nature. We demonstrate the spontaneous emergence of modularity in a population of individuals that evolve in a changing environment. We show that the level of modularity correlates with the rapidity and severity of environmental change. The modularity arises as a synergistic response to the noise in the environment in the presence of horizontal gene transfer. We suggest that the hierarchical structure observed in the natural world may be a broken symmetry state, which generically results from evolution in a changing environment. To support our results, we analyze experimental protein interaction data and show that protein interaction networks became increasingly modular as evolution proceeded over the last four billion years. We also discuss a method to determine the divergence time of a protein.
[ { "created": "Mon, 23 Feb 2009 21:57:28 GMT", "version": "v1" } ]
2009-11-13
[ [ "He", "Jiankui", "" ], [ "Sun", "Jun", "" ], [ "Deem", "Michael W.", "" ] ]
We investigate the selective forces that promote the emergence of modularity in nature. We demonstrate the spontaneous emergence of modularity in a population of individuals that evolve in a changing environment. We show that the level of modularity correlates with the rapidity and severity of environmental change. The modularity arises as a synergistic response to the noise in the environment in the presence of horizontal gene transfer. We suggest that the hierarchical structure observed in the natural world may be a broken symmetry state, which generically results from evolution in a changing environment. To support our results, we analyze experimental protein interaction data and show that protein interaction networks became increasingly modular as evolution proceeded over the last four billion years. We also discuss a method to determine the divergence time of a protein.
0809.1716
Philippe Rondard
Philippe Rondard (IGF), Siluo Huang (IGF), Carine Monnier (IGF), Haijun Tu, Bertrand Blanchard (IGF), Nadia Oueslati (IGF), Fanny Malhaire (IGF), Ying Li, Eric Trinquet (IGF), Gilles Labesse (CBS), Jean-Philippe Pin (IGF), Jianfeng Liu (IGF)
Functioning of the dimeric GABA(B) receptor extracellular domain revealed by glycan wedge scanning
null
The EMBO Journal 27, 9 (2008) 1321-1332
10.1038/emboj.2008.64
null
q-bio.NC q-bio.BM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The G-protein-coupled receptor (GPCR) activated by the neurotransmitter GABA is made up of two subunits, GABA(B1) and GABA(B2). GABA(B1) binds agonists, whereas GABA(B2) is required for trafficking GABA(B1) to the cell surface, increasing agonist affinity to GABA(B1), and activating associated G proteins. These subunits each comprise two domains, a Venus flytrap domain (VFT) and a heptahelical transmembrane domain (7TM). How agonist binding to the GABA(B1) VFT leads to GABA(B2) 7TM activation remains unknown. Here, we used a glycan wedge scanning approach to investigate how the GABA(B) VFT dimer controls receptor activity. We first identified the dimerization interface using a bioinformatics approach and then showed that introducing an N-glycan at this interface prevents the association of the two subunits and abolishes all activities of GABA(B2), including agonist activation of the G protein. We also identified a second region in the VFT where insertion of an N-glycan does not prevent dimerization, but blocks agonist activation of the receptor. These data provide new insight into the function of this prototypical GPCR and demonstrate that a change in the dimerization interface is required for receptor activation.
[ { "created": "Wed, 10 Sep 2008 07:04:23 GMT", "version": "v1" } ]
2008-09-11
[ [ "Rondard", "Philippe", "", "IGF" ], [ "Huang", "Siluo", "", "IGF" ], [ "Monnier", "Carine", "", "IGF" ], [ "Tu", "Haijun", "", "IGF" ], [ "Blanchard", "Bertrand", "", "IGF" ], [ "Oueslati", "Nadia", "", "IGF" ], [ "Malhaire", "Fanny", "", "IGF" ], [ "Li", "Ying", "", "IGF" ], [ "Trinquet", "Eric", "", "IGF" ], [ "Labesse", "Gilles", "", "CBS" ], [ "Pin", "Jean-Philippe", "", "IGF" ], [ "Liu", "Jianfeng", "", "IGF" ] ]
The G-protein-coupled receptor (GPCR) activated by the neurotransmitter GABA is made up of two subunits, GABA(B1) and GABA(B2). GABA(B1) binds agonists, whereas GABA(B2) is required for trafficking GABA(B1) to the cell surface, increasing agonist affinity to GABA(B1), and activating associated G proteins. These subunits each comprise two domains, a Venus flytrap domain (VFT) and a heptahelical transmembrane domain (7TM). How agonist binding to the GABA(B1) VFT leads to GABA(B2) 7TM activation remains unknown. Here, we used a glycan wedge scanning approach to investigate how the GABA(B) VFT dimer controls receptor activity. We first identified the dimerization interface using a bioinformatics approach and then showed that introducing an N-glycan at this interface prevents the association of the two subunits and abolishes all activities of GABA(B2), including agonist activation of the G protein. We also identified a second region in the VFT where insertion of an N-glycan does not prevent dimerization, but blocks agonist activation of the receptor. These data provide new insight into the function of this prototypical GPCR and demonstrate that a change in the dimerization interface is required for receptor activation.
1112.6015
Suleiman Khan
Suleiman A. Khan, Ali Faisal, John Patric Mpindi, Juuso A. Parkkinen, Tuomo Kalliokoski, Antti Poso, Olli P. Kallioniemi, Krister Wennerberg, Samuel Kaski
Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs
10 pages, 7 figures, 2 tables
null
null
null
q-bio.BM stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed these biological response profiles into components, each linked to a characteristic chemical descriptor profile. The integrated quantitative analysis of the chemical and biological spaces was more informative about protein-target based drug similarity than either dataset separately. We identified ten major components that link distinct VolSurf features across multiple compounds to specific biological activity types. For example, component 2 (hydrophobic properties) strongly links to DNA damage response, while component 3 (hydrogen bonding) connects to metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides. In summary, our approach identified specific chemical structures shared across multiple drugs causing distinct biological responses. The decoding of such systematic chemical-biological relationships is necessary to build better models of drug effects, including unidentified types of molecular properties with strong biological effects.
[ { "created": "Tue, 27 Dec 2011 20:40:19 GMT", "version": "v1" } ]
2011-12-30
[ [ "Khan", "Suleiman A.", "" ], [ "Faisal", "Ali", "" ], [ "Mpindi", "John Patric", "" ], [ "Parkkinen", "Juuso A.", "" ], [ "Kalliokoski", "Tuomo", "" ], [ "Poso", "Antti", "" ], [ "Kallioniemi", "Olli P.", "" ], [ "Wennerberg", "Krister", "" ], [ "Kaski", "Samuel", "" ] ]
Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed these biological response profiles into components, each linked to a characteristic chemical descriptor profile. The integrated quantitative analysis of the chemical and biological spaces was more informative about protein-target based drug similarity than either dataset separately. We identified ten major components that link distinct VolSurf features across multiple compounds to specific biological activity types. For example, component 2 (hydrophobic properties) strongly links to DNA damage response, while component 3 (hydrogen bonding) connects to metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides. In summary, our approach identified specific chemical structures shared across multiple drugs causing distinct biological responses. The decoding of such systematic chemical-biological relationships is necessary to build better models of drug effects, including unidentified types of molecular properties with strong biological effects.
2310.08913
Zhenyu Han
Zhenyu Han, Qianyue Hao, Qiwei He, Katherine Budeski, Depeng Jin, Fengli Xu, Kun Tang
How enlightened self-interest guided global vaccine sharing benefits all: a modelling study
Accepted by Journal of Global Health
null
null
null
q-bio.PE physics.soc-ph
http://creativecommons.org/licenses/by-sa/4.0/
Background: Despite the consensus that vaccines play an important role in combating the global spread of infectious diseases, vaccine inequity is still rampant with deep-seated mentality of self-priority. This study aims to evaluate the existence and possible outcomes of a more equitable global vaccine distribution and explore a concrete incentive mechanism that promotes vaccine equity. Methods: We design a metapopulation epidemiological model that simultaneously considers global vaccine distribution and human mobility, which is then calibrated by the number of infections and real-world vaccination records during COVID-19 pandemic from March 2020 to July 2021. We explore the possibility of the enlightened self-interest incentive mechanism, i.e., improving one's own epidemic outcomes by sharing vaccines with other countries, by evaluating the number of infections and deaths under various vaccine sharing strategies using the proposed model. To understand how these strategies affect the national interests, we distinguish the imported and local cases for further cost-benefit analyses that rationalize the enlightened self-interest incentive mechanism behind vaccine sharing. ...
[ { "created": "Fri, 13 Oct 2023 07:37:22 GMT", "version": "v1" } ]
2023-10-16
[ [ "Han", "Zhenyu", "" ], [ "Hao", "Qianyue", "" ], [ "He", "Qiwei", "" ], [ "Budeski", "Katherine", "" ], [ "Jin", "Depeng", "" ], [ "Xu", "Fengli", "" ], [ "Tang", "Kun", "" ] ]
Background: Despite the consensus that vaccines play an important role in combating the global spread of infectious diseases, vaccine inequity is still rampant with deep-seated mentality of self-priority. This study aims to evaluate the existence and possible outcomes of a more equitable global vaccine distribution and explore a concrete incentive mechanism that promotes vaccine equity. Methods: We design a metapopulation epidemiological model that simultaneously considers global vaccine distribution and human mobility, which is then calibrated by the number of infections and real-world vaccination records during COVID-19 pandemic from March 2020 to July 2021. We explore the possibility of the enlightened self-interest incentive mechanism, i.e., improving one's own epidemic outcomes by sharing vaccines with other countries, by evaluating the number of infections and deaths under various vaccine sharing strategies using the proposed model. To understand how these strategies affect the national interests, we distinguish the imported and local cases for further cost-benefit analyses that rationalize the enlightened self-interest incentive mechanism behind vaccine sharing. ...
1506.05583
Michael Assaf
Tommaso Biancalani and Michael Assaf
Genetic Toggle Switch in the Absence of Cooperative Binding: Exact Results
12 pages, 4 figures. To appear in Phys. Rev. Lett. (2015)
Phys. Rev. Lett. 115, 208101 (2015)
10.1103/PhysRevLett.115.208101
null
q-bio.MN cond-mat.stat-mech
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an analytical treatment of a genetic switch model consisting of two mutually inhibiting genes operating without cooperative binding of the corresponding transcription factors. Previous studies have numerically shown that these systems can exhibit bimodal dynamics without possessing two stable fixed points at the deterministic level. We analytically show that bimodality is induced by the noise and find the critical repression strength that controls a transition between the bimodal and non-bimodal regimes. We also identify characteristic polynomial scaling laws of the mean switching time between bimodal states. These results, independent of the model under study, reveal essential differences between these systems and systems with cooperative binding, where there is no critical threshold for bimodality and the mean switching time scales exponentially with the system size.
[ { "created": "Thu, 18 Jun 2015 08:42:27 GMT", "version": "v1" }, { "created": "Thu, 22 Oct 2015 10:52:28 GMT", "version": "v2" } ]
2015-11-18
[ [ "Biancalani", "Tommaso", "" ], [ "Assaf", "Michael", "" ] ]
We present an analytical treatment of a genetic switch model consisting of two mutually inhibiting genes operating without cooperative binding of the corresponding transcription factors. Previous studies have numerically shown that these systems can exhibit bimodal dynamics without possessing two stable fixed points at the deterministic level. We analytically show that bimodality is induced by the noise and find the critical repression strength that controls a transition between the bimodal and non-bimodal regimes. We also identify characteristic polynomial scaling laws of the mean switching time between bimodal states. These results, independent of the model under study, reveal essential differences between these systems and systems with cooperative binding, where there is no critical threshold for bimodality and the mean switching time scales exponentially with the system size.
q-bio/0512040
Gurinder Atwal
Gurinder Singh Atwal, William Bialek
Ambiguous model learning made unambiguous with 1/f priors
8 pages, 2 figures
NIPS 16, MIT Press, Cambridge (2004)
null
null
q-bio.OT q-bio.NC
null
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the answer depends on the prior expectations of the dynamics of the model parameter that is to be inferred from the data. Local time constraints on the priors are insufficient to pick one interpretation over another. On the other hand, nonlocal time constraints, induced by a $1/f$ noise spectrum of the priors, is shown to permit learning of a specific model parameter even when there are infinitely many equally plausible interpretations of the data. This transition is inferred by a remarkable mapping of the model estimation problem to a dissipative physical system, allowing the use of powerful statistical mechanical methods to uncover the transition from indeterminate to determinate model learning.
[ { "created": "Fri, 23 Dec 2005 06:25:39 GMT", "version": "v1" } ]
2007-05-23
[ [ "Atwal", "Gurinder Singh", "" ], [ "Bialek", "William", "" ] ]
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the answer depends on the prior expectations of the dynamics of the model parameter that is to be inferred from the data. Local time constraints on the priors are insufficient to pick one interpretation over another. On the other hand, nonlocal time constraints, induced by a $1/f$ noise spectrum of the priors, is shown to permit learning of a specific model parameter even when there are infinitely many equally plausible interpretations of the data. This transition is inferred by a remarkable mapping of the model estimation problem to a dissipative physical system, allowing the use of powerful statistical mechanical methods to uncover the transition from indeterminate to determinate model learning.
2009.03808
Jo\~ao Gondim
Jo\~ao A. M. Gondim
Preventing epidemics by wearing masks: An application to COVID-19
null
null
10.1016/j.chaos.2020.110599
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The goal of this work is to consider widespread use of face masks as a non-pharmaceutical control strategy for the Covid-19 pandemic. A SEIR model that divides the population into individuals that wear masks and those that do not is considered. After calculating the basic reproductive number by a next generation approach, a criterion for determining when an epidemic can be prevented by the use of masks only and the critical percentage of mask users for disease prevention in the population are derived. The results are then applied to real world data from the United States, Brazil and Italy.
[ { "created": "Tue, 8 Sep 2020 15:04:07 GMT", "version": "v1" } ]
2021-02-03
[ [ "Gondim", "João A. M.", "" ] ]
The goal of this work is to consider widespread use of face masks as a non-pharmaceutical control strategy for the Covid-19 pandemic. A SEIR model that divides the population into individuals that wear masks and those that do not is considered. After calculating the basic reproductive number by a next generation approach, a criterion for determining when an epidemic can be prevented by the use of masks only and the critical percentage of mask users for disease prevention in the population are derived. The results are then applied to real world data from the United States, Brazil and Italy.
q-bio/0504004
Rudolf A. Roemer
Daphne Klotsa, Rudolf A. Roemer, Matthew S. Turner
Electronic Transport in DNA
12 pages RevTeX4 with 17 figures, submitted to Biophysical Journal
Biophys. J. 89, 2187-2198 (2005)
10.1529/biophysj.105.064014
CSC-106
q-bio.GN cond-mat.soft q-bio.BM
null
We study the electronic properties of DNA by way of a tight-binding model applied to four particular DNA sequences. The charge transfer properties are presented in terms of localisation lengths, crudely speaking the length over which electrons travel. Various types of disorder, including random potentials, are employed to account for different real environments. We have performed calculations on poly(dG)-poly(dC), telomeric-DNA, random-ATGC DNA and lambda-DNA. We find that random and lambda-DNA have localisation lengths allowing for electron motion among a few dozen base pairs only. A novel enhancement of localisation lengths is observed at particular energies for an increasing binary backbone disorder. We comment on the possible biological relevance of sequence dependent charge transfer in DNA.
[ { "created": "Mon, 4 Apr 2005 15:18:47 GMT", "version": "v1" } ]
2007-05-23
[ [ "Klotsa", "Daphne", "" ], [ "Roemer", "Rudolf A.", "" ], [ "Turner", "Matthew S.", "" ] ]
We study the electronic properties of DNA by way of a tight-binding model applied to four particular DNA sequences. The charge transfer properties are presented in terms of localisation lengths, crudely speaking the length over which electrons travel. Various types of disorder, including random potentials, are employed to account for different real environments. We have performed calculations on poly(dG)-poly(dC), telomeric-DNA, random-ATGC DNA and lambda-DNA. We find that random and lambda-DNA have localisation lengths allowing for electron motion among a few dozen base pairs only. A novel enhancement of localisation lengths is observed at particular energies for an increasing binary backbone disorder. We comment on the possible biological relevance of sequence dependent charge transfer in DNA.
1311.2255
Roberto Natalini
Ezio Di Costanzo, Roberto Natalini, Luigi Preziosi
A hybrid mathematical model for self-organizing cell migration in the zebrafish lateral line
null
Journal of Mathematical Biology (2015) 71: 171
10.1007/s00285-014-0812-9
null
q-bio.CB q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we propose a "discrete in continuous" mathematical model for the morphogenesis of the posterior lateral line system in zebrafishes. Our model follows closely the results obtained in recent biological experiments. We rely on a hybrid description: discrete for the cellular level and continuous for the molecular level. We prove the existence of steady solutions consistent with the formation of particular biological structure, the neuromasts. Dynamical numerical simulations are performed to show the behavior of the model and its qualitative and quantitative accuracy to describe the evolution of the cell aggregate.
[ { "created": "Sun, 10 Nov 2013 09:47:59 GMT", "version": "v1" } ]
2017-05-29
[ [ "Di Costanzo", "Ezio", "" ], [ "Natalini", "Roberto", "" ], [ "Preziosi", "Luigi", "" ] ]
In this paper we propose a "discrete in continuous" mathematical model for the morphogenesis of the posterior lateral line system in zebrafishes. Our model follows closely the results obtained in recent biological experiments. We rely on a hybrid description: discrete for the cellular level and continuous for the molecular level. We prove the existence of steady solutions consistent with the formation of particular biological structure, the neuromasts. Dynamical numerical simulations are performed to show the behavior of the model and its qualitative and quantitative accuracy to describe the evolution of the cell aggregate.
q-bio/0501037
Reka Albert
Madalena Chaves, Reka Albert and Eduardo D. Sontag
Robustness and fragility of Boolean models for genetic regulatory networks
29 pages, 5 figures, accepted to the Journal of Theoretical Biology
Journal of Theoretical Biology 235, 431-449 (2005)
null
null
q-bio.MN
null
Interactions between genes and gene products give rise to complex circuits that enable cells to process information and respond to external signals. Theoretical studies often describe these interactions using continuous, stochastic, or logical approaches. We propose a new modeling framework for gene regulatory networks, that combines the intuitive appeal of a qualitative description of gene states with a high flexibility in incorporating stochasticity in the duration of cellular processes. We apply our methods to the regulatory network of the segment polarity genes, thus gaining novel insights into the development of gene expression patterns. For example, we show that very short synthesis and decay times can perturb the wild type pattern. On the other hand, separation of timescales between pre- and posttranslational processes and a minimal prepattern ensure convergence to the wild type expression pattern regardless of fluctuations.
[ { "created": "Thu, 27 Jan 2005 22:27:38 GMT", "version": "v1" } ]
2007-05-23
[ [ "Chaves", "Madalena", "" ], [ "Albert", "Reka", "" ], [ "Sontag", "Eduardo D.", "" ] ]
Interactions between genes and gene products give rise to complex circuits that enable cells to process information and respond to external signals. Theoretical studies often describe these interactions using continuous, stochastic, or logical approaches. We propose a new modeling framework for gene regulatory networks, that combines the intuitive appeal of a qualitative description of gene states with a high flexibility in incorporating stochasticity in the duration of cellular processes. We apply our methods to the regulatory network of the segment polarity genes, thus gaining novel insights into the development of gene expression patterns. For example, we show that very short synthesis and decay times can perturb the wild type pattern. On the other hand, separation of timescales between pre- and posttranslational processes and a minimal prepattern ensure convergence to the wild type expression pattern regardless of fluctuations.
1608.05367
Og DeSouza
Og DeSouza, Elio Tuci, Octavio Miramontes
Fruitful symbioses between termites and computers
13 pages, 4 figures, 1 table. Unrevised version. This is a review drawing heavily from arXiv:1410.0930, arXiv:1404.6267, arXiv:1404.6267. This is an excerpt of a talk given by ODS at The 14th International Conference on the Simulation of Adaptive Behavior 23-26 August 2016, Aberystwyth, UK
null
null
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The living-together of distinct organisms in a single termite nest along with the termite builder colony, is emblematic in its ecological and evolutionary significance. On top of preserving biodiversity, these interspecific and intraspecific symbioses provide useful examples of interindividual associations thought to underly transitions in organic evolution. Being interindividual in nature, such processes may involve emergent phenomena and hence call for analytical solutions provided by computing tools and modelling, as opposed to classical biological methods of analysis. Here we provide selected examples of such solutions, showing that termite studies may profit from a symbiotic-like link with computing science to open up wide and new research avenues in ecology and evolution.
[ { "created": "Thu, 18 Aug 2016 18:31:37 GMT", "version": "v1" } ]
2016-08-19
[ [ "DeSouza", "Og", "" ], [ "Tuci", "Elio", "" ], [ "Miramontes", "Octavio", "" ] ]
The living-together of distinct organisms in a single termite nest along with the termite builder colony, is emblematic in its ecological and evolutionary significance. On top of preserving biodiversity, these interspecific and intraspecific symbioses provide useful examples of interindividual associations thought to underly transitions in organic evolution. Being interindividual in nature, such processes may involve emergent phenomena and hence call for analytical solutions provided by computing tools and modelling, as opposed to classical biological methods of analysis. Here we provide selected examples of such solutions, showing that termite studies may profit from a symbiotic-like link with computing science to open up wide and new research avenues in ecology and evolution.
2309.11642
Hongli Ni
Hongli Ni, Chinmayee Prabhu Dessai, Haonan Lin, Wei Wang, Shaoxiong Chen, Yuhao Yuan, Xiaowei Ge, Jianpeng Ao, Nolan Vild, Ji-Xin Cheng
High-content stimulated Raman histology of human breast cancer
6 figures
null
null
null
q-bio.TO eess.IV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Histological examination is crucial for cancer diagnosis, including hematoxylin and eosin (H&E) staining for mapping morphology and immunohistochemistry (IHC) staining for revealing chemical information. Recently developed two-color stimulated Raman histology could bypass the complex tissue processing to mimic H&E-like morphology. Yet, the underlying chemical features are not revealed, compromising the effectiveness of prognostic stratification. Here, we present a high-content stimulated Raman histology (HC-SRH) platform that provides both morphological and chemical information for cancer diagnosis based on un-stained breast tissues. Through spectral unmixing in the C-H vibration window, HC-SRH can map unsaturated lipids, cellular protein, extracellular matrix, saturated lipid, and water in breast tissue. In this way, HC-SRH provides excellent contrast for various tissue components. Considering rapidness is important in clinical trials, we implemented spectral selective sampling to boost the speed of HC-SRH by one order. We also successfully demonstrated the HC-SRH in a clinical-compatible fiber laser-based SRS microscopy. With the widely rapid tuning capability of the advanced fiber laser, a clear chemical contrast of nucleic acid and solid-state ester is shown in the fingerprint result.
[ { "created": "Wed, 20 Sep 2023 21:11:53 GMT", "version": "v1" } ]
2023-09-22
[ [ "Ni", "Hongli", "" ], [ "Dessai", "Chinmayee Prabhu", "" ], [ "Lin", "Haonan", "" ], [ "Wang", "Wei", "" ], [ "Chen", "Shaoxiong", "" ], [ "Yuan", "Yuhao", "" ], [ "Ge", "Xiaowei", "" ], [ "Ao", "Jianpeng", "" ], [ "Vild", "Nolan", "" ], [ "Cheng", "Ji-Xin", "" ] ]
Histological examination is crucial for cancer diagnosis, including hematoxylin and eosin (H&E) staining for mapping morphology and immunohistochemistry (IHC) staining for revealing chemical information. Recently developed two-color stimulated Raman histology could bypass the complex tissue processing to mimic H&E-like morphology. Yet, the underlying chemical features are not revealed, compromising the effectiveness of prognostic stratification. Here, we present a high-content stimulated Raman histology (HC-SRH) platform that provides both morphological and chemical information for cancer diagnosis based on un-stained breast tissues. Through spectral unmixing in the C-H vibration window, HC-SRH can map unsaturated lipids, cellular protein, extracellular matrix, saturated lipid, and water in breast tissue. In this way, HC-SRH provides excellent contrast for various tissue components. Considering rapidness is important in clinical trials, we implemented spectral selective sampling to boost the speed of HC-SRH by one order. We also successfully demonstrated the HC-SRH in a clinical-compatible fiber laser-based SRS microscopy. With the widely rapid tuning capability of the advanced fiber laser, a clear chemical contrast of nucleic acid and solid-state ester is shown in the fingerprint result.
0805.0532
Szymon {\L}{\ke}ski
Szymon Leski, Daniel K. Wojcik
Inferring coupling strength from event-related dynamics
Final version published in Phys Rev E
Phys. Rev. E 78, 041918 (2008)
10.1103/PhysRevE.78.041918
null
q-bio.NC nlin.CD
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose an approach for inferring strength of coupling between two systems from their transient dynamics. This is of vital importance in cases where most information is carried by the transients, for instance in evoked potentials measured commonly in electrophysiology. We show viability of our approach using nonlinear and linear measures of synchronization on a population model of thalamocortical loop and on a system of two coupled Roessler-type oscillators in non-chaotic regime.
[ { "created": "Mon, 5 May 2008 14:13:42 GMT", "version": "v1" }, { "created": "Thu, 27 Nov 2008 10:39:22 GMT", "version": "v2" } ]
2008-11-27
[ [ "Leski", "Szymon", "" ], [ "Wojcik", "Daniel K.", "" ] ]
We propose an approach for inferring strength of coupling between two systems from their transient dynamics. This is of vital importance in cases where most information is carried by the transients, for instance in evoked potentials measured commonly in electrophysiology. We show viability of our approach using nonlinear and linear measures of synchronization on a population model of thalamocortical loop and on a system of two coupled Roessler-type oscillators in non-chaotic regime.
1801.03721
Ushasi Roy
C. S. Renadheer, Ushasi Roy, Manoj Gopalakrishnan
A path-integral formulation of the run and tumble motion and chemotaxis in Escherichia coli
22 pages, major reorganization of sections, additional figure added, few errors corrected
null
10.1088/1751-8121/ab5425
null
q-bio.QM physics.bio-ph q-bio.CB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bacteria such as Escherichia coli move about in a series of runs and tumbles: while a run state (straight motion) entails all the flagellar motors spinning in counterclockwise mode, a tumble is caused by a shift in the state of one or more motors to clockwise spinning mode. In the presence of an attractant gradient in the environment, runs in the favourable direction are extended, and this results in a net drift of the organism in the direction of the gradient. The underlying signal transduction mechanism produces directed motion through a bi-lobed response function which relates the clockwise bias of the flagellar motor to temporal changes in the attractant concentration. The two lobes (positive and negative) of the response function are separated by a time interval of $\sim 1$s, such that the bacterium effectively compares the concentration at two different positions in space and responds accordingly. We present here a novel path-integral method which allows us to address this problem in the most general way possible, including multi-step CW-CCW transitions, directional persistence and power-law waiting time distributions. The method allows us to calculate quantities such as the effective diffusion coefficient and drift velocity, in a power series expansion in the attractant gradient. Explicit results in the lowest order in the expansion are presented for specific models, which, wherever applicable, agree with the known results. New results for gamma-distributed run interval distributions are also presented.
[ { "created": "Thu, 11 Jan 2018 11:36:37 GMT", "version": "v1" }, { "created": "Tue, 20 Feb 2018 10:33:40 GMT", "version": "v2" }, { "created": "Fri, 23 Feb 2018 09:07:38 GMT", "version": "v3" } ]
2020-01-08
[ [ "Renadheer", "C. S.", "" ], [ "Roy", "Ushasi", "" ], [ "Gopalakrishnan", "Manoj", "" ] ]
Bacteria such as Escherichia coli move about in a series of runs and tumbles: while a run state (straight motion) entails all the flagellar motors spinning in counterclockwise mode, a tumble is caused by a shift in the state of one or more motors to clockwise spinning mode. In the presence of an attractant gradient in the environment, runs in the favourable direction are extended, and this results in a net drift of the organism in the direction of the gradient. The underlying signal transduction mechanism produces directed motion through a bi-lobed response function which relates the clockwise bias of the flagellar motor to temporal changes in the attractant concentration. The two lobes (positive and negative) of the response function are separated by a time interval of $\sim 1$s, such that the bacterium effectively compares the concentration at two different positions in space and responds accordingly. We present here a novel path-integral method which allows us to address this problem in the most general way possible, including multi-step CW-CCW transitions, directional persistence and power-law waiting time distributions. The method allows us to calculate quantities such as the effective diffusion coefficient and drift velocity, in a power series expansion in the attractant gradient. Explicit results in the lowest order in the expansion are presented for specific models, which, wherever applicable, agree with the known results. New results for gamma-distributed run interval distributions are also presented.
2006.08867
Anna Heffernan
Annalisa Riccardi, Jessica Gemignani, Francisco Fern\'andez-Navarro, Anna Heffernan
Optimisation of non-pharmaceutical measures in COVID-19 growth via neural networks
This work has been accepted for publication by IEEE Transactions on Emerging Topics in Computational Intelligence. \copyright 2020 IEEE
IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 5, no. 1, pp. 79-91, Feb. 2021
10.1109/TETCI.2020.3046012
null
q-bio.OT q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
On 19th March, the World Health Organisation declared a pandemic. Through this global spread, many nations have witnessed exponential growth of confirmed cases brought under control by severe mass quarantine or lockdown measures. However, some have, through a different timeline of actions, prevented this exponential growth. Currently as some continue to tackle growth, others attempt to safely lift restrictions whilst avoiding a resurgence. This study seeks to quantify the impact of government actions in mitigating viral transmission of SARS-CoV-2 by a novel soft computing approach that makes concurrent use of a neural network model, to predict the daily slope increase of cumulative infected, and an optimiser, with a parametrisation of the government restriction time series, to understanding the best set of mitigating actions. Data for two territories, Italy and Taiwan, have been gathered to model government restrictions in traveling, testing and enforcement of social distance measures as well as people connectivity and adherence to government actions. It is found that a larger and earlier testing campaign with tighter entry restrictions benefit both regions, resulting in significantly less confirmed cases. Interestingly, this scenario couples with an earlier but milder implementation of nationwide restrictions for Italy, thus supporting Taiwan's lack of nationwide lockdown. The results, found with a purely data-driven approach, are in line with the main findings of mathematical epidemiological models, proving that the proposed approach has value and that the data alone contains valuable knowledge to inform decision makers.
[ { "created": "Tue, 16 Jun 2020 02:04:40 GMT", "version": "v1" }, { "created": "Tue, 14 Jul 2020 21:04:03 GMT", "version": "v2" }, { "created": "Wed, 25 Nov 2020 20:54:07 GMT", "version": "v3" }, { "created": "Wed, 16 Dec 2020 00:29:43 GMT", "version": "v4" } ]
2022-09-28
[ [ "Riccardi", "Annalisa", "" ], [ "Gemignani", "Jessica", "" ], [ "Fernández-Navarro", "Francisco", "" ], [ "Heffernan", "Anna", "" ] ]
On 19th March, the World Health Organisation declared a pandemic. Through this global spread, many nations have witnessed exponential growth of confirmed cases brought under control by severe mass quarantine or lockdown measures. However, some have, through a different timeline of actions, prevented this exponential growth. Currently as some continue to tackle growth, others attempt to safely lift restrictions whilst avoiding a resurgence. This study seeks to quantify the impact of government actions in mitigating viral transmission of SARS-CoV-2 by a novel soft computing approach that makes concurrent use of a neural network model, to predict the daily slope increase of cumulative infected, and an optimiser, with a parametrisation of the government restriction time series, to understanding the best set of mitigating actions. Data for two territories, Italy and Taiwan, have been gathered to model government restrictions in traveling, testing and enforcement of social distance measures as well as people connectivity and adherence to government actions. It is found that a larger and earlier testing campaign with tighter entry restrictions benefit both regions, resulting in significantly less confirmed cases. Interestingly, this scenario couples with an earlier but milder implementation of nationwide restrictions for Italy, thus supporting Taiwan's lack of nationwide lockdown. The results, found with a purely data-driven approach, are in line with the main findings of mathematical epidemiological models, proving that the proposed approach has value and that the data alone contains valuable knowledge to inform decision makers.
2009.10693
Alex McAvoy
Kamran Kaveh, Alex McAvoy, Krishnendu Chatterjee, Martin A. Nowak
The Moran process on 2-chromatic graphs
19 pages
PLOS Computational Biology (2020)
10.1371/journal.pcbi.1008402
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Resources are rarely distributed uniformly within a population. Heterogeneity in the concentration of a drug, the quality of breeding sites, or wealth can all affect evolutionary dynamics. In this study, we represent a collection of properties affecting the fitness at a given location using a color. A green node is rich in resources while a red node is poorer. More colors can represent a broader spectrum of resource qualities. For a population evolving according to the birth-death Moran model, the first question we address is which structures, identified by graph connectivity and graph coloring, are evolutionarily equivalent. We prove that all properly two-colored, undirected, regular graphs are evolutionarily equivalent (where "properly colored" means that no two neighbors have the same color). We then compare the effects of background heterogeneity on properly two-colored graphs to those with alternative schemes in which the colors are permuted. Finally, we discuss dynamic coloring as a model for spatiotemporal resource fluctuations, and we illustrate that random dynamic colorings often diminish the effects of background heterogeneity relative to a proper two-coloring.
[ { "created": "Tue, 22 Sep 2020 17:10:42 GMT", "version": "v1" } ]
2022-02-18
[ [ "Kaveh", "Kamran", "" ], [ "McAvoy", "Alex", "" ], [ "Chatterjee", "Krishnendu", "" ], [ "Nowak", "Martin A.", "" ] ]
Resources are rarely distributed uniformly within a population. Heterogeneity in the concentration of a drug, the quality of breeding sites, or wealth can all affect evolutionary dynamics. In this study, we represent a collection of properties affecting the fitness at a given location using a color. A green node is rich in resources while a red node is poorer. More colors can represent a broader spectrum of resource qualities. For a population evolving according to the birth-death Moran model, the first question we address is which structures, identified by graph connectivity and graph coloring, are evolutionarily equivalent. We prove that all properly two-colored, undirected, regular graphs are evolutionarily equivalent (where "properly colored" means that no two neighbors have the same color). We then compare the effects of background heterogeneity on properly two-colored graphs to those with alternative schemes in which the colors are permuted. Finally, we discuss dynamic coloring as a model for spatiotemporal resource fluctuations, and we illustrate that random dynamic colorings often diminish the effects of background heterogeneity relative to a proper two-coloring.
1809.09707
Doo Seok Jeong
Doo Seok Jeong
Tutorial: Neuromorphic spiking neural networks for temporal learning
40 pages, 10 figures
null
10.1063/1.5042243
null
q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Spiking neural networks (SNN) as time-dependent hypotheses consisting of spiking nodes (neurons) and directed edges (synapses) are believed to offer unique solutions to reward prediction tasks and the related feedback that are classified as reinforcement learning. Generally, temporal difference (TD) learning renders it possible to optimize a model network to predict the delayed reward in an ad hoc manner. Neuromorphic SNNs--networks built using dedicated hardware--particularly leverage such TD learning for not only reward prediction but also temporal sequence prediction in a physical time domain. In this tutorial, such learning in a physical time domain is referred to as temporal learning to distinguish it from conventional TD learning-based methods that generally involve algorithmic (rather than physical) time. This tutorial addresses neuromorphic SNNs for temporal learning from the scratch. It first concerns general characteristics of SNNs including spiking neurons and information coding schemes and then moves on to temporal learning including its general concept, feasible algorithms, and their association with neurophysiological learning rules that have intensively been enriched for the last few decades.
[ { "created": "Tue, 11 Sep 2018 06:32:42 GMT", "version": "v1" } ]
2018-10-17
[ [ "Jeong", "Doo Seok", "" ] ]
Spiking neural networks (SNN) as time-dependent hypotheses consisting of spiking nodes (neurons) and directed edges (synapses) are believed to offer unique solutions to reward prediction tasks and the related feedback that are classified as reinforcement learning. Generally, temporal difference (TD) learning renders it possible to optimize a model network to predict the delayed reward in an ad hoc manner. Neuromorphic SNNs--networks built using dedicated hardware--particularly leverage such TD learning for not only reward prediction but also temporal sequence prediction in a physical time domain. In this tutorial, such learning in a physical time domain is referred to as temporal learning to distinguish it from conventional TD learning-based methods that generally involve algorithmic (rather than physical) time. This tutorial addresses neuromorphic SNNs for temporal learning from the scratch. It first concerns general characteristics of SNNs including spiking neurons and information coding schemes and then moves on to temporal learning including its general concept, feasible algorithms, and their association with neurophysiological learning rules that have intensively been enriched for the last few decades.
1911.06946
Yu Sun
Xi Fu, Dan Norback, Qianqian Yuan, Yanling Li, Xunhua Zhu, Yiqun Deng, Jamal Hisham Hashim, Zailina Hashim, Yi-Wu Zheng, Xu-Xin Lai, Michael Dho Spangfort, Yu Sun
Indoor microbiome, environmental characteristics and asthma among junior high school students in Johor Bahru, Malaysia
56 pages,1 figure, 3 supplemental figures, 9 supplemental tables
null
10.1016/j.envint.2020.105664
null
q-bio.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Indoor microbial diversity and composition are suggested to affect the prevalence and severity of asthma. In this study, we collected floor dust and environmental characteristics from 21 classrooms, and health data related to asthma symptoms from 309 students, in junior high schools in Johor Bahru, Malaysia. Bacterial and fungal composition was characterized by sequencing 16s rRNA gene and internal transcribed spacer (ITS) region, and the absolute microbial concentration was quantified by qPCR. In total, 326 bacterial and 255 fungal genera were characterized. Five bacterial (Sphingobium, Rhodomicrobium, Shimwellia, Solirubrobacter, Pleurocapsa) and two fungal (Torulaspora and Leptosphaeriaceae) taxa were protective for asthma severity. Two bacterial taxa, Izhakiella and Robinsoniella, were positively associated with asthma severity. Several protective bacterial taxa including Rhodomicrobium, Shimwellia and Sphingobium has been reported as protective microbes in previous studies, whereas other taxa were first time reported. Environmental characteristics, such as age of building, size of textile curtain per room volume, occurrence of cockroaches, concentration of house dust mite allergens transferred from homes by the occupants, were involved in shaping the overall microbial community but not asthma-associated taxa; whereas visible dampness and mold, which did not change the overall microbial community for floor dust, decreased the concentration of protective bacteria Rhodomicrobium (\b{eta}=-2.86, p=0.021) of asthma, indicating complex interactions between microbes, environmental characteristics and asthma symptoms. Overall, this is the first indoor microbiome study to characterize the asthma-associated microbes and their environmental determinant in tropical area, promoting the understanding of microbial exposure and respiratory health in this region.
[ { "created": "Sat, 16 Nov 2019 03:23:07 GMT", "version": "v1" } ]
2020-03-24
[ [ "Fu", "Xi", "" ], [ "Norback", "Dan", "" ], [ "Yuan", "Qianqian", "" ], [ "Li", "Yanling", "" ], [ "Zhu", "Xunhua", "" ], [ "Deng", "Yiqun", "" ], [ "Hashim", "Jamal Hisham", "" ], [ "Hashim", "Zailina", "" ], [ "Zheng", "Yi-Wu", "" ], [ "Lai", "Xu-Xin", "" ], [ "Spangfort", "Michael Dho", "" ], [ "Sun", "Yu", "" ] ]
Indoor microbial diversity and composition are suggested to affect the prevalence and severity of asthma. In this study, we collected floor dust and environmental characteristics from 21 classrooms, and health data related to asthma symptoms from 309 students, in junior high schools in Johor Bahru, Malaysia. Bacterial and fungal composition was characterized by sequencing 16s rRNA gene and internal transcribed spacer (ITS) region, and the absolute microbial concentration was quantified by qPCR. In total, 326 bacterial and 255 fungal genera were characterized. Five bacterial (Sphingobium, Rhodomicrobium, Shimwellia, Solirubrobacter, Pleurocapsa) and two fungal (Torulaspora and Leptosphaeriaceae) taxa were protective for asthma severity. Two bacterial taxa, Izhakiella and Robinsoniella, were positively associated with asthma severity. Several protective bacterial taxa including Rhodomicrobium, Shimwellia and Sphingobium has been reported as protective microbes in previous studies, whereas other taxa were first time reported. Environmental characteristics, such as age of building, size of textile curtain per room volume, occurrence of cockroaches, concentration of house dust mite allergens transferred from homes by the occupants, were involved in shaping the overall microbial community but not asthma-associated taxa; whereas visible dampness and mold, which did not change the overall microbial community for floor dust, decreased the concentration of protective bacteria Rhodomicrobium (\b{eta}=-2.86, p=0.021) of asthma, indicating complex interactions between microbes, environmental characteristics and asthma symptoms. Overall, this is the first indoor microbiome study to characterize the asthma-associated microbes and their environmental determinant in tropical area, promoting the understanding of microbial exposure and respiratory health in this region.
1804.05129
Amparo Ba\'illo
Amparo Ba\'illo and Jos\'e Enrique Chac\'on
A survey and a new selection criterion for statistical home range estimation
18 figures
null
null
null
q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The home range of a specific animal describes the geographic area where this individual spends most of the time while carrying out its usual activities (eating, resting, reproduction, ...). Although a well-established definition of this concept is lacking, there is a variety of home range estimators. The first objective of this work is to review and categorize the statistical methodologies proposed in the literature to approximate the home range of an animal, based on a sample of observed locations. The second aim is to address the open question of choosing the "best" home range from a collection of them based on the same sample. We introduce a numerical index, based on a penalization criterion, to rank the estimated home ranges. The key idea is to balance the excess area covered by the estimator (with respect to the original sample) and a shape descriptor measuring the over-adjustment of the home range to the data. To our knowledge, apart from computing the home range area, our ranking procedure is the first one which is both applicable to real data and to any type of home range estimator. Further, the optimization of the selection index provides in fact a way to select the smoothing parameter for the kernel home range estimator. For clarity of exposition, we have applied all the estimation procedures and our selection proposal to a set of real locations of a Mongolian wolf using R as the statistical software. As a byproduct, this review contains a thorough revision of the implementation of home range estimators in the R language.
[ { "created": "Fri, 13 Apr 2018 21:50:03 GMT", "version": "v1" } ]
2018-04-17
[ [ "Baíllo", "Amparo", "" ], [ "Chacón", "José Enrique", "" ] ]
The home range of a specific animal describes the geographic area where this individual spends most of the time while carrying out its usual activities (eating, resting, reproduction, ...). Although a well-established definition of this concept is lacking, there is a variety of home range estimators. The first objective of this work is to review and categorize the statistical methodologies proposed in the literature to approximate the home range of an animal, based on a sample of observed locations. The second aim is to address the open question of choosing the "best" home range from a collection of them based on the same sample. We introduce a numerical index, based on a penalization criterion, to rank the estimated home ranges. The key idea is to balance the excess area covered by the estimator (with respect to the original sample) and a shape descriptor measuring the over-adjustment of the home range to the data. To our knowledge, apart from computing the home range area, our ranking procedure is the first one which is both applicable to real data and to any type of home range estimator. Further, the optimization of the selection index provides in fact a way to select the smoothing parameter for the kernel home range estimator. For clarity of exposition, we have applied all the estimation procedures and our selection proposal to a set of real locations of a Mongolian wolf using R as the statistical software. As a byproduct, this review contains a thorough revision of the implementation of home range estimators in the R language.
1007.5075
Greg Gloor Dr
Gregory B. Gloor, Ruben Hummelen, Jean M. Macklaim, Russell J. Dickson, Andrew D. Fernandes, Roderick MacPhee, Gregor Reid
Microbiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products
28 pages, 13 figures
null
10.1371/journal.pone.0015406
null
q-bio.GN q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end. The number of reads generated permitted saturating or near-saturating analysis of samples of the vaginal microbiome. The large number of reads al- lowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an ob- servation that has significant implications for sequence clustering of similar high-throughput data. We show that the short reads are sufficient to assign organisms to the genus or species level in most cases. We suggest that this method will be useful for the deep sequencing of any short nucleotide region that is taxonomically informative; these include the V3, V5 regions of the bac- terial 16S rRNA genes and the eukaryotic V9 region that is gaining popularity for sampling protist diversity.
[ { "created": "Wed, 28 Jul 2010 21:17:22 GMT", "version": "v1" } ]
2014-04-16
[ [ "Gloor", "Gregory B.", "" ], [ "Hummelen", "Ruben", "" ], [ "Macklaim", "Jean M.", "" ], [ "Dickson", "Russell J.", "" ], [ "Fernandes", "Andrew D.", "" ], [ "MacPhee", "Roderick", "" ], [ "Reid", "Gregor", "" ] ]
We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end. The number of reads generated permitted saturating or near-saturating analysis of samples of the vaginal microbiome. The large number of reads al- lowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an ob- servation that has significant implications for sequence clustering of similar high-throughput data. We show that the short reads are sufficient to assign organisms to the genus or species level in most cases. We suggest that this method will be useful for the deep sequencing of any short nucleotide region that is taxonomically informative; these include the V3, V5 regions of the bac- terial 16S rRNA genes and the eukaryotic V9 region that is gaining popularity for sampling protist diversity.
1710.06953
Naoto Hori
Jorjethe Roca, Naoto Hori, Yogambigai Velmurugu, Ranjani Narayanan, Prasanth Narayanan, D. Thirumalai, Anjum Ansari
Monovalent ions modulate the flux through multiple folding pathways of an RNA pseudoknot
Supporting Information included
null
10.1073/pnas.1717582115
null
q-bio.BM cond-mat.soft physics.bio-ph physics.chem-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The functions of RNA pseudoknots (PKs), which are minimal tertiary structural motifs and an integral part of several ribozymes and ribonucleoprotein complexes, are determined by their structure, stability and dynamics. Therefore, it is important to elucidate the general principles governing their thermodynamics/folding mechanisms. Here, we combine experiments and simulations to examine the folding/unfolding pathways of the VPK pseudoknot, a variant of the Mouse Mammary Tumor Virus (MMTV) PK involved in ribosomal frameshifting. Fluorescent nucleotide analogs (2-aminopurine and pyrrolocytidine) placed at different stem/loop positions in the PK, and laser temperature-jump approaches serve as local probes allowing us to monitor the order of assembly of VPK with two helices with different intrinsic stabilities. The experiments and molecular simulations show that at 50 mM KCl the dominant folding pathway populates only the more stable partially folded hairpin. As the salt concentration is increased a parallel folding pathway emerges, involving the less stable hairpin structure as an alternate intermediate. Notably, the flux between the pathways is modulated by the ionic strength. The findings support the principle that the order of PK structure formation is determined by the relative stabilities of the hairpins, which can be altered by sequence variations or salt concentrations. Our study not only unambiguously demonstrates that PK folds by parallel pathways, but also establishes that quantitative description of RNA self-assembly requires a synergistic combination of experiments and simulations.
[ { "created": "Wed, 18 Oct 2017 22:48:36 GMT", "version": "v1" } ]
2022-10-12
[ [ "Roca", "Jorjethe", "" ], [ "Hori", "Naoto", "" ], [ "Velmurugu", "Yogambigai", "" ], [ "Narayanan", "Ranjani", "" ], [ "Narayanan", "Prasanth", "" ], [ "Thirumalai", "D.", "" ], [ "Ansari", "Anjum", "" ] ]
The functions of RNA pseudoknots (PKs), which are minimal tertiary structural motifs and an integral part of several ribozymes and ribonucleoprotein complexes, are determined by their structure, stability and dynamics. Therefore, it is important to elucidate the general principles governing their thermodynamics/folding mechanisms. Here, we combine experiments and simulations to examine the folding/unfolding pathways of the VPK pseudoknot, a variant of the Mouse Mammary Tumor Virus (MMTV) PK involved in ribosomal frameshifting. Fluorescent nucleotide analogs (2-aminopurine and pyrrolocytidine) placed at different stem/loop positions in the PK, and laser temperature-jump approaches serve as local probes allowing us to monitor the order of assembly of VPK with two helices with different intrinsic stabilities. The experiments and molecular simulations show that at 50 mM KCl the dominant folding pathway populates only the more stable partially folded hairpin. As the salt concentration is increased a parallel folding pathway emerges, involving the less stable hairpin structure as an alternate intermediate. Notably, the flux between the pathways is modulated by the ionic strength. The findings support the principle that the order of PK structure formation is determined by the relative stabilities of the hairpins, which can be altered by sequence variations or salt concentrations. Our study not only unambiguously demonstrates that PK folds by parallel pathways, but also establishes that quantitative description of RNA self-assembly requires a synergistic combination of experiments and simulations.
1604.05082
Haralambos Hatzikirou
J. C. L. Alfonso and A. Kohn-Luque and T. Stylianopoulos and F. Feuerhake and A. Deutsch and H. Hatzikirou
Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights
null
null
null
null
q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve functional tumour-associated blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation medi- ated by vascular targeting agents that induce occlusion/collapse of tumour blood vessels. In contrast, the therapeutic intention of normalising the abnormal structure and function of tumour vascular net- works, e.g. via alleviating stress-induced vaso-occlusion, is to improve chemo-, immuno- and radiation therapy efficacy. Although both strategies have shown therapeutic potential, it remains unclear why they often fail to control glioma invasion into the surrounding healthy brain tissue. To shed light on this issue, we propose a mathematical model of glioma invasion focusing on the interplay between the mi- gration/proliferation dichotomy (Go-or-Grow) of glioma cells and modulations of the functional tumour vasculature. Vaso-modulatory interventions are modelled by varying the degree of vaso-occlusion. We discovered the existence of a critical cell proliferation/diffusion ratio that separates glioma invasion re- sponses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the tumour front speed and increase the infiltration width, for those in the other regime the invasion speed increases and infiltration width decreases. We show how these in silico findings can be used to guide individualised approaches of vaso-modulatory treatment strategies and thereby improve success rates.
[ { "created": "Mon, 18 Apr 2016 10:56:59 GMT", "version": "v1" } ]
2016-04-19
[ [ "Alfonso", "J. C. L.", "" ], [ "Kohn-Luque", "A.", "" ], [ "Stylianopoulos", "T.", "" ], [ "Feuerhake", "F.", "" ], [ "Deutsch", "A.", "" ], [ "Hatzikirou", "H.", "" ] ]
There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve functional tumour-associated blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation medi- ated by vascular targeting agents that induce occlusion/collapse of tumour blood vessels. In contrast, the therapeutic intention of normalising the abnormal structure and function of tumour vascular net- works, e.g. via alleviating stress-induced vaso-occlusion, is to improve chemo-, immuno- and radiation therapy efficacy. Although both strategies have shown therapeutic potential, it remains unclear why they often fail to control glioma invasion into the surrounding healthy brain tissue. To shed light on this issue, we propose a mathematical model of glioma invasion focusing on the interplay between the mi- gration/proliferation dichotomy (Go-or-Grow) of glioma cells and modulations of the functional tumour vasculature. Vaso-modulatory interventions are modelled by varying the degree of vaso-occlusion. We discovered the existence of a critical cell proliferation/diffusion ratio that separates glioma invasion re- sponses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the tumour front speed and increase the infiltration width, for those in the other regime the invasion speed increases and infiltration width decreases. We show how these in silico findings can be used to guide individualised approaches of vaso-modulatory treatment strategies and thereby improve success rates.
1309.0765
Fernando Antoneli Jr
Fernando Antoneli, Renata C. Ferreira, Marcelo R. S. Briones
A Model of Gene Expression Based on Random Dynamical Systems Reveals Modularity Properties of Gene Regulatory Networks
34 pages, 6 figures
Mathematical Biosciences, Volume 276, June 2016, Pages 82-100
10.1016/j.mbs.2016.03.008
null
q-bio.MN math.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model.
[ { "created": "Tue, 3 Sep 2013 18:18:26 GMT", "version": "v1" }, { "created": "Thu, 8 May 2014 19:07:25 GMT", "version": "v2" }, { "created": "Sun, 18 Jan 2015 17:13:44 GMT", "version": "v3" }, { "created": "Fri, 24 Apr 2015 13:13:46 GMT", "version": "v4" }, { "created": "Mon, 28 Dec 2015 17:57:15 GMT", "version": "v5" }, { "created": "Sun, 20 Mar 2016 14:33:45 GMT", "version": "v6" } ]
2016-07-11
[ [ "Antoneli", "Fernando", "" ], [ "Ferreira", "Renata C.", "" ], [ "Briones", "Marcelo R. S.", "" ] ]
Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model.
0704.3640
Dennis Wylie
Dennis Cates Wylie
Linked by Loops: Network Structure and Switch Integration in Complex Dynamical Systems
21 pages, 5 figures. Paper simplified and shortened. Quantities presented in table 1 are different, though related, to quantities previously presented in table 1
null
null
null
q-bio.QM cond-mat.dis-nn math.DS nlin.CD
null
Simple nonlinear dynamical systems with multiple stable stationary states are often taken as models for switchlike biological systems. This paper considers the interaction of multiple such simple multistable systems when they are embedded together into a larger dynamical "supersystem." Attention is focused on the network structure of the resulting set of coupled differential equations, and the consequences of this structure on the propensity of the embedded switches to act independently versus cooperatively. Specifically, it is argued that both larger average and larger variance of the node degree distribution lead to increased switch independence. Given the frequency of empirical observations of high variance degree distributions (e.g., power-law) in biological networks, it is suggested that the results presented here may aid in identifying switch-integrating subnetworks as comparatively homogenous, low-degree, substructures. Potential applications to ecological problems such as the relationship of stability and complexity are also briefly discussed.
[ { "created": "Thu, 26 Apr 2007 23:24:28 GMT", "version": "v1" }, { "created": "Fri, 13 Jul 2007 01:51:03 GMT", "version": "v2" }, { "created": "Tue, 22 Jan 2008 18:57:14 GMT", "version": "v3" }, { "created": "Thu, 10 Apr 2008 20:34:39 GMT", "version": "v4" } ]
2008-04-10
[ [ "Wylie", "Dennis Cates", "" ] ]
Simple nonlinear dynamical systems with multiple stable stationary states are often taken as models for switchlike biological systems. This paper considers the interaction of multiple such simple multistable systems when they are embedded together into a larger dynamical "supersystem." Attention is focused on the network structure of the resulting set of coupled differential equations, and the consequences of this structure on the propensity of the embedded switches to act independently versus cooperatively. Specifically, it is argued that both larger average and larger variance of the node degree distribution lead to increased switch independence. Given the frequency of empirical observations of high variance degree distributions (e.g., power-law) in biological networks, it is suggested that the results presented here may aid in identifying switch-integrating subnetworks as comparatively homogenous, low-degree, substructures. Potential applications to ecological problems such as the relationship of stability and complexity are also briefly discussed.
1108.2664
Christopher Whidden
Chris Whidden, Robert G. Beiko, and Norbert Zeh
Fixed-Parameter and Approximation Algorithms for Maximum Agreement Forests
36 pages, 9 figures. Removed the Approximation and TBR sections and simplified the Hybridization section. To appear in SIAM Journal on Computing
null
null
null
q-bio.PE cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present new and improved fixed-parameter algorithms for computing maximum agreement forests (MAFs) of pairs of rooted binary phylogenetic trees. The size of such a forest for two trees corresponds to their subtree prune-and-regraft distance and, if the agreement forest is acyclic, to their hybridization number. These distance measures are essential tools for understanding reticulate evolution. Our algorithm for computing maximum acyclic agreement forests is the first depth-bounded search algorithm for this problem. Our algorithms substantially outperform the best previous algorithms for these problems.
[ { "created": "Fri, 12 Aug 2011 17:20:39 GMT", "version": "v1" }, { "created": "Thu, 2 May 2013 14:53:59 GMT", "version": "v2" } ]
2015-03-19
[ [ "Whidden", "Chris", "" ], [ "Beiko", "Robert G.", "" ], [ "Zeh", "Norbert", "" ] ]
We present new and improved fixed-parameter algorithms for computing maximum agreement forests (MAFs) of pairs of rooted binary phylogenetic trees. The size of such a forest for two trees corresponds to their subtree prune-and-regraft distance and, if the agreement forest is acyclic, to their hybridization number. These distance measures are essential tools for understanding reticulate evolution. Our algorithm for computing maximum acyclic agreement forests is the first depth-bounded search algorithm for this problem. Our algorithms substantially outperform the best previous algorithms for these problems.
1401.4289
Ralph Brinks
Ralph Brinks
Incidence, recovery and prevalence of infectious diseases: non-parametric disease model and application to influenza in Germany
14 pages, 9 figures
null
null
null
q-bio.PE q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work we describe a non-parametric disease model that links the temporal change of the prevalence of an infectious disease to the incidence and the recovery rates. The model is only based on the common epidemiological measures incidence and recovery rate. As an application, the model is used to calculate the prevalence of influenza in Germany for a hypothetical birth cohort during 2001 and 2013.
[ { "created": "Fri, 17 Jan 2014 10:02:26 GMT", "version": "v1" } ]
2014-01-20
[ [ "Brinks", "Ralph", "" ] ]
In this work we describe a non-parametric disease model that links the temporal change of the prevalence of an infectious disease to the incidence and the recovery rates. The model is only based on the common epidemiological measures incidence and recovery rate. As an application, the model is used to calculate the prevalence of influenza in Germany for a hypothetical birth cohort during 2001 and 2013.
1409.7941
David Holcman
K. Reynaud Z. Schuss, N. Rouach, D. Holcman
Why so many sperm cells?
6 pages
null
null
null
q-bio.CB physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A key limiting step in fertility is the search for the oocyte by spermatozoa. Initially, there are tens of millions of sperm cells, but a single one will make it to the oocyte. This may be one of the most severe selection processes designed by evolution, whose role is yet to be understood. Why is it that such a huge redundancy is required and what does that mean for the search process? we propose to discuss here these questions and consequently a new line of interdisciplinary research needed to find possible answers.
[ { "created": "Sun, 28 Sep 2014 18:44:45 GMT", "version": "v1" } ]
2014-09-30
[ [ "Schuss", "K. Reynaud Z.", "" ], [ "Rouach", "N.", "" ], [ "Holcman", "D.", "" ] ]
A key limiting step in fertility is the search for the oocyte by spermatozoa. Initially, there are tens of millions of sperm cells, but a single one will make it to the oocyte. This may be one of the most severe selection processes designed by evolution, whose role is yet to be understood. Why is it that such a huge redundancy is required and what does that mean for the search process? we propose to discuss here these questions and consequently a new line of interdisciplinary research needed to find possible answers.
1712.03926
Margaret Cheung
Fabio C. Zegarra, Dirar Homouz, Yossi Eliaz, Andrei G. Gasic, and Margaret S. Cheung
The impact of hydrodynamic interactions on protein folding rates depends on temperature
11 figures
Phys. Rev. E 97, 032402 (2018)
10.1103/PhysRevE.97.032402
null
q-bio.BM physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigated the impact of hydrodynamic interactions (HI) on protein folding using a coarse-grained model. The extent of the impact of hydrodynamic interactions, whether it accelerates, retards, or has no effect on protein folding, has been controversial. Together with a theoretical framework of the energy landscape theory (ELT) for protein folding that describes the dynamics of the collective motion with a single reaction coordinate across a folding barrier, we compared the kinetic effects of HI on the folding rates of two protein models that use a chain of single beads with distinctive topologies: a 64-residue alpha/beta chymotrypsin inhibitor 2 (CI2) protein, and a 57-residue beta-barrel alpha-spectrin src-Homology 3 domain (SH3) protein. When comparing the protein folding kinetics simulated with Brownian dynamics in the presence of HI to that in the absence of HI, we find that the effect of HI on protein folding appears to have a crossover behavior about the folding temperature. Meaning that at a temperature greater than the folding temperature, the enhanced friction from the hydrodynamic solvents between the beads in an unfolded configuration results in lowered folding rate; conversely, at a temperature lower than the folding temperature, HI accelerates folding by the backflow of solvent toward the native folded state. Additionally, the extent of acceleration depends on the topology of a protein: for a protein like CI2, where its folding nucleus is rather diffuse in a transition state, HI channels the formation of contacts by favoring a major folding pathway in a complex free energy landscape, thus accelerating folding. For a protein like SH3, where its folding nucleus is already specific and less diffuse, HI matters less at a temperature lower than the folding temperature. Our findings provide further theoretical insight to protein folding kinetic experiments and simulations.
[ { "created": "Mon, 11 Dec 2017 18:12:55 GMT", "version": "v1" }, { "created": "Tue, 12 Dec 2017 12:21:27 GMT", "version": "v2" } ]
2018-03-14
[ [ "Zegarra", "Fabio C.", "" ], [ "Homouz", "Dirar", "" ], [ "Eliaz", "Yossi", "" ], [ "Gasic", "Andrei G.", "" ], [ "Cheung", "Margaret S.", "" ] ]
We investigated the impact of hydrodynamic interactions (HI) on protein folding using a coarse-grained model. The extent of the impact of hydrodynamic interactions, whether it accelerates, retards, or has no effect on protein folding, has been controversial. Together with a theoretical framework of the energy landscape theory (ELT) for protein folding that describes the dynamics of the collective motion with a single reaction coordinate across a folding barrier, we compared the kinetic effects of HI on the folding rates of two protein models that use a chain of single beads with distinctive topologies: a 64-residue alpha/beta chymotrypsin inhibitor 2 (CI2) protein, and a 57-residue beta-barrel alpha-spectrin src-Homology 3 domain (SH3) protein. When comparing the protein folding kinetics simulated with Brownian dynamics in the presence of HI to that in the absence of HI, we find that the effect of HI on protein folding appears to have a crossover behavior about the folding temperature. Meaning that at a temperature greater than the folding temperature, the enhanced friction from the hydrodynamic solvents between the beads in an unfolded configuration results in lowered folding rate; conversely, at a temperature lower than the folding temperature, HI accelerates folding by the backflow of solvent toward the native folded state. Additionally, the extent of acceleration depends on the topology of a protein: for a protein like CI2, where its folding nucleus is rather diffuse in a transition state, HI channels the formation of contacts by favoring a major folding pathway in a complex free energy landscape, thus accelerating folding. For a protein like SH3, where its folding nucleus is already specific and less diffuse, HI matters less at a temperature lower than the folding temperature. Our findings provide further theoretical insight to protein folding kinetic experiments and simulations.
1806.01541
Charlotte Recapet
Charlotte R\'ecapet (ECOBIOP), Lise Dauphin, Lisa Jacquin (EDB), Julien Gasparini (IEES), Anne-Caroline Prevot-Julliard (UP11)
Eumelanin-based colouration reflects local survival of juvenile feral pigeons in an urban pigeon house
null
Journal of Avian Biology, Wiley, 2013, 44 (6), pp.583 - 590
10.1111/j.1600-048X.2013.00087.x
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Urbanisation introduces deep changes in habitats, eventually creating new urban ecosystems where ecological functions are driven by human activities. The higher frequency of some phenotypes in urban vs rural/wild areas has led to the assumption that directional selection in urban habitats occurs, which may thereby favour some behavioural and physiological traits in urban animal populations compared to rural ones. However, empirical evidence of directional selection on phenotypic traits in urban areas remains scarce. In this study we tested whether eumelanin-based colouration could be linked to survival in two urban populations of the feral pigeon Columba livia. A number of studies in different cities pointed out a higher frequency of darker individuals in more urbanised areas compared to rural ones. To investigate whether directional selection through survival on this highly heritable trait could explain such patterns, we conducted mark-recapture studies on two populations of feral pigeons in highly urbanized areas. We predicted that darker coloured individuals would exhibit higher survival and/or philopatry (integrated into 'local survival') than paler coloured ones. No difference in local survival was found between adults of different colouration intensities. However, on one site, we found that darker juveniles had a higher local survival probability than light ones. Juvenile local survival on that site was also negatively correlated with the number of chicks born. This suggests the existence of colour- and/or density-dependent selection processes acting on juvenile feral pigeons in urban environments, acting through differential mortality and/or dispersal.
[ { "created": "Tue, 5 Jun 2018 08:11:30 GMT", "version": "v1" } ]
2018-06-22
[ [ "Récapet", "Charlotte", "", "ECOBIOP" ], [ "Dauphin", "Lise", "", "EDB" ], [ "Jacquin", "Lisa", "", "EDB" ], [ "Gasparini", "Julien", "", "IEES" ], [ "Prevot-Julliard", "Anne-Caroline", "", "UP11" ] ]
Urbanisation introduces deep changes in habitats, eventually creating new urban ecosystems where ecological functions are driven by human activities. The higher frequency of some phenotypes in urban vs rural/wild areas has led to the assumption that directional selection in urban habitats occurs, which may thereby favour some behavioural and physiological traits in urban animal populations compared to rural ones. However, empirical evidence of directional selection on phenotypic traits in urban areas remains scarce. In this study we tested whether eumelanin-based colouration could be linked to survival in two urban populations of the feral pigeon Columba livia. A number of studies in different cities pointed out a higher frequency of darker individuals in more urbanised areas compared to rural ones. To investigate whether directional selection through survival on this highly heritable trait could explain such patterns, we conducted mark-recapture studies on two populations of feral pigeons in highly urbanized areas. We predicted that darker coloured individuals would exhibit higher survival and/or philopatry (integrated into 'local survival') than paler coloured ones. No difference in local survival was found between adults of different colouration intensities. However, on one site, we found that darker juveniles had a higher local survival probability than light ones. Juvenile local survival on that site was also negatively correlated with the number of chicks born. This suggests the existence of colour- and/or density-dependent selection processes acting on juvenile feral pigeons in urban environments, acting through differential mortality and/or dispersal.
1709.05987
Helene Leman
Helene Leman
A stochastic model for reproductive isolation under asymmetrical mating preferences
null
null
null
null
q-bio.PE math.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
More and more evidence shows that mating preference is a mechanism that may lead to a reproductive isolation event. In this paper, a haploid population living on two patches linked by migration is considered. Individuals are ecologically and demographically neutral on the space and differ only on a trait, $a$ or $A$, affecting both mating success and migration rate. The special feature of this paper is to assume that the strengths of the mating preference and the migration depend on the trait carried. Indeed, patterns of mating preferences are generally asymmetrical between the subspecies of a population. I prove that mating preference interacting with frequency-dependent migration behavior can lead to a reproductive isolation. Then, I describe the time before reproductive isolation occurs. To reach this result, I use an original method to study the limiting dynamical system, analyzing first the system without migration and adding migration with a perturbation method. Finally, I study how the time before reproductive isolation is influenced by the parameters of migration and of mating preferences, highlighting that large migration rates tend to favor types with weak mating preferences.
[ { "created": "Mon, 18 Sep 2017 14:53:44 GMT", "version": "v1" }, { "created": "Sun, 6 May 2018 10:05:52 GMT", "version": "v2" } ]
2018-05-08
[ [ "Leman", "Helene", "" ] ]
More and more evidence shows that mating preference is a mechanism that may lead to a reproductive isolation event. In this paper, a haploid population living on two patches linked by migration is considered. Individuals are ecologically and demographically neutral on the space and differ only on a trait, $a$ or $A$, affecting both mating success and migration rate. The special feature of this paper is to assume that the strengths of the mating preference and the migration depend on the trait carried. Indeed, patterns of mating preferences are generally asymmetrical between the subspecies of a population. I prove that mating preference interacting with frequency-dependent migration behavior can lead to a reproductive isolation. Then, I describe the time before reproductive isolation occurs. To reach this result, I use an original method to study the limiting dynamical system, analyzing first the system without migration and adding migration with a perturbation method. Finally, I study how the time before reproductive isolation is influenced by the parameters of migration and of mating preferences, highlighting that large migration rates tend to favor types with weak mating preferences.
1907.04765
Junqing Tang
Han Hu, Junqing Tang, Yi Wang, Hongfeng Zhang, Dong Wu, Yingchun Lin, Lina Su, Yan Liu, Wei Zhang, Chao Wang, Xiaomin Wu
Evaluating bird collision risk of a high-speed railway crossing the habitat of the crested ibis (Nipponia nippon) in Qinling Mountains, China
25 pages, 6 figures, preprint for submission to Transportation Research Part D: Transport and Environment
null
null
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bird collisions with high-speed transport modes is a vital topic on vehicle safety and wildlife protection, especially when high-speed trains, with an average speed of 250km/h, have to run across the habitat of an endangered bird species. This paper evaluates the bird-train collision risk associated with a recent high-speed railway project in Qinling Mountains, China, for the crested ibis (Nipponia nippon) and other local bird species. Using line transect surveys and walking monitoring techniques, we surveyed the population abundance, spatial-temporal distributions, and bridge-crossing behaviors of the birds in the study area. The results show that: (1) The crested ibis and the egret were the two most abundant waterfowl species in the study area. The RAI of these two species were about 43.69% and 42.91%, respectively; (2) Crested ibises overall habitat closer to the railway bridge. 91.63% of them were firstly detected within the range of 0m to 25m of the vicinity of the bridge; (3) the ratio between crossing over and under the railway bridge was about 7:3. Crested ibises were found to prefer to fly over the railway bridge (89.29% of the total crossing activities observed for this species). Egrets were more likely to cross the railway below the bridge, and they accounted for 60.27% of the total observations of crossing under the bridge. We recommend that, while the collision risk of crested ibises could be low, barrier-like structures, such as fences, should still be considered to promote the conservation of multiple bird species in the area. This paper provides a practical case for railway ecology studies in China. To our best knowledge, this is the first high-speed railway project that takes protecting crested ibises as one of the top priorities, and exemplifies the recent nationwide initiative towards the construction of "eco-civilization" in the country.
[ { "created": "Wed, 10 Jul 2019 14:52:48 GMT", "version": "v1" } ]
2019-07-11
[ [ "Hu", "Han", "" ], [ "Tang", "Junqing", "" ], [ "Wang", "Yi", "" ], [ "Zhang", "Hongfeng", "" ], [ "Wu", "Dong", "" ], [ "Lin", "Yingchun", "" ], [ "Su", "Lina", "" ], [ "Liu", "Yan", "" ], [ "Zhang", "Wei", "" ], [ "Wang", "Chao", "" ], [ "Wu", "Xiaomin", "" ] ]
Bird collisions with high-speed transport modes is a vital topic on vehicle safety and wildlife protection, especially when high-speed trains, with an average speed of 250km/h, have to run across the habitat of an endangered bird species. This paper evaluates the bird-train collision risk associated with a recent high-speed railway project in Qinling Mountains, China, for the crested ibis (Nipponia nippon) and other local bird species. Using line transect surveys and walking monitoring techniques, we surveyed the population abundance, spatial-temporal distributions, and bridge-crossing behaviors of the birds in the study area. The results show that: (1) The crested ibis and the egret were the two most abundant waterfowl species in the study area. The RAI of these two species were about 43.69% and 42.91%, respectively; (2) Crested ibises overall habitat closer to the railway bridge. 91.63% of them were firstly detected within the range of 0m to 25m of the vicinity of the bridge; (3) the ratio between crossing over and under the railway bridge was about 7:3. Crested ibises were found to prefer to fly over the railway bridge (89.29% of the total crossing activities observed for this species). Egrets were more likely to cross the railway below the bridge, and they accounted for 60.27% of the total observations of crossing under the bridge. We recommend that, while the collision risk of crested ibises could be low, barrier-like structures, such as fences, should still be considered to promote the conservation of multiple bird species in the area. This paper provides a practical case for railway ecology studies in China. To our best knowledge, this is the first high-speed railway project that takes protecting crested ibises as one of the top priorities, and exemplifies the recent nationwide initiative towards the construction of "eco-civilization" in the country.
2403.15282
Carmen Molina-Paris
Giulia Belluccini, Qianying Lin, Bevelynn Williams, Yijun Lou, Zati Vatansever, Mart\'in L\'opez-Garc\'ia, Grant Lythe, Thomas Leitner, Ethan Romero-Severson, Carmen Molina-Par\'is
A story of viral co-infection, co-transmission and co-feeding in ticks: how to compute an invasion reproduction number
37 pages and 4 figures
null
null
null
q-bio.PE q-bio.QM
http://creativecommons.org/licenses/by/4.0/
With a single circulating vector-borne virus, the basic reproduction number incorporates contributions from tick-to-tick (co-feeding), tick-to-host and host-to-tick transmission routes. With two different circulating vector-borne viral strains, resident and invasive, and under the assumption that co-feeding is the only transmission route in a tick population, the invasion reproduction number depends on whether the model system of ordinary differential equations possesses the property of neutrality. We show that a simple model, with two populations of ticks infected with one strain, resident or invasive, and one population of co-infected ticks, does not have Alizon's neutrality property. We present model alternatives that are capable of representing the invasion potential of a novel strain by including populations of ticks dually infected with the same strain. The invasion reproduction number is analysed with the next-generation method and via numerical simulations.
[ { "created": "Fri, 22 Mar 2024 15:26:05 GMT", "version": "v1" } ]
2024-03-25
[ [ "Belluccini", "Giulia", "" ], [ "Lin", "Qianying", "" ], [ "Williams", "Bevelynn", "" ], [ "Lou", "Yijun", "" ], [ "Vatansever", "Zati", "" ], [ "López-García", "Martín", "" ], [ "Lythe", "Grant", "" ], [ "Leitner", "Thomas", "" ], [ "Romero-Severson", "Ethan", "" ], [ "Molina-París", "Carmen", "" ] ]
With a single circulating vector-borne virus, the basic reproduction number incorporates contributions from tick-to-tick (co-feeding), tick-to-host and host-to-tick transmission routes. With two different circulating vector-borne viral strains, resident and invasive, and under the assumption that co-feeding is the only transmission route in a tick population, the invasion reproduction number depends on whether the model system of ordinary differential equations possesses the property of neutrality. We show that a simple model, with two populations of ticks infected with one strain, resident or invasive, and one population of co-infected ticks, does not have Alizon's neutrality property. We present model alternatives that are capable of representing the invasion potential of a novel strain by including populations of ticks dually infected with the same strain. The invasion reproduction number is analysed with the next-generation method and via numerical simulations.
2308.05514
Julia Theresa Kamml
Julia Kamml, Claire Acevedo, David Kammer
Advanced-Glycation Endproducts: How cross-linking properties affect the collagen fibril behavior
19 pages, 10 figures
null
null
null
q-bio.TO
http://creativecommons.org/licenses/by/4.0/
Advanced-Glycation-Endproducts (AGEs) are known to be a major cause of impaired tissue material properties. In collagen fibrils, the main building component of human tissue, these AGEs appear as fibrillar cross-links. When AGEs accumulate in collagen fibrils, a process often caused by diabetes and aging, the mechanical properties of the collagen fibril are altered. However, current knowledge about the mechanical properties of different types of AGEs, and their quantity in collagen fibrils is limited owing to the scarcity of available experimental data. Consequently, the precise relationship between the nano-scale cross-link properties, their density in collagen fibrils, and the mechanical properties of the collagen fibrils at larger scales remains poorly understood. In our study, we use coarse-grained molecular dynamics simulations and perform destructive tensile tests on collagen fibrils to evaluate the effect of different cross-link densities and their mechanical properties on collagen fibril deformation and fracture behavior. We observe that the collagen fibril stiffens at high strain levels when either the AGEs density or the loading energy capacity of AGEs are increased. We demonstrate that this stiffening is caused by a mechanism that favors energy absorption via stretching rather than inter-molecular sliding. Hence, in cross-linked collagen fibrils, the absorbed energy is stored rather than dissipated through friction, resulting in brittle fracture upon fibrillar failure. Further, by varying multiple AGEs nano-scale parameters, we show that the AGEs loading energy capacity is, aside from their density in the fibril, the unique factor determining the effect of different types of AGEs on the mechanical behavior of collagen fibrils. Our results show that knowing AGEs properties is crucial for understanding of the origin of impaired tissue behavior.
[ { "created": "Thu, 10 Aug 2023 11:55:44 GMT", "version": "v1" } ]
2023-08-11
[ [ "Kamml", "Julia", "" ], [ "Acevedo", "Claire", "" ], [ "Kammer", "David", "" ] ]
Advanced-Glycation-Endproducts (AGEs) are known to be a major cause of impaired tissue material properties. In collagen fibrils, the main building component of human tissue, these AGEs appear as fibrillar cross-links. When AGEs accumulate in collagen fibrils, a process often caused by diabetes and aging, the mechanical properties of the collagen fibril are altered. However, current knowledge about the mechanical properties of different types of AGEs, and their quantity in collagen fibrils is limited owing to the scarcity of available experimental data. Consequently, the precise relationship between the nano-scale cross-link properties, their density in collagen fibrils, and the mechanical properties of the collagen fibrils at larger scales remains poorly understood. In our study, we use coarse-grained molecular dynamics simulations and perform destructive tensile tests on collagen fibrils to evaluate the effect of different cross-link densities and their mechanical properties on collagen fibril deformation and fracture behavior. We observe that the collagen fibril stiffens at high strain levels when either the AGEs density or the loading energy capacity of AGEs are increased. We demonstrate that this stiffening is caused by a mechanism that favors energy absorption via stretching rather than inter-molecular sliding. Hence, in cross-linked collagen fibrils, the absorbed energy is stored rather than dissipated through friction, resulting in brittle fracture upon fibrillar failure. Further, by varying multiple AGEs nano-scale parameters, we show that the AGEs loading energy capacity is, aside from their density in the fibril, the unique factor determining the effect of different types of AGEs on the mechanical behavior of collagen fibrils. Our results show that knowing AGEs properties is crucial for understanding of the origin of impaired tissue behavior.
1406.1400
Maria Antony Dhivyan Joseph Eugene Mr
Maria Antony Dhivyan JE
The Structural Biology and Critical Evaluation of Bacterial Proteases as Targets in New Drug Design
85 pages, 3 sequencing results
null
null
null
q-bio.BM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bacteria produce a range of proteolytic enzymes, for which a number human equivalent or structurally similar examples exist and the primary focus of this study was to analyse the published literature to find proteolytic enzymes, specifically endoproteses and to examine the similarity in the substrates that they act on so as to predict a suitable structural motif which can be used as the basis for preparation of useful prodrug carriers against diseases caused by specific bacteria like Salmonella. Also, the similarities between the bacterial proteases and the action of human matrix metalloproteinases (MMPs), together with the MMP-like activity of bacterial endoproteases to activate human MMPs, were also analysed. This information was used to try to identify substrates on which the MMPs and bacterial proteases act, to aid the design of oligopeptide prodrug carriers to treat cancer and its metastatic spread. MMPs are greatly involved in cancer growth and progression, a few MMPs and certain proteases share a similar type of activity in degrading the extra cellular matrix (ECM) and substrates including gelatin. Our primary targets of study were to identify the proteases and MMPs that facilitate the migration of bacteria and growth of tumour cells respectively. The study was thus a two-way approach to study the substrate specificity of both bacterial proteases and MMPs, thereby to help in characterisation of their substrates. Various bioinformatics tools were used in the characterisation of the proteases and substrates as well as in the identification of possible binding sites and conserved regions in a range of candidate proteins. Central to this project was the salmonella derived PgtE surface protease that has been shown recently to act upon the pro-forms of human MMP-9.
[ { "created": "Tue, 3 Jun 2014 04:29:57 GMT", "version": "v1" } ]
2014-06-06
[ [ "JE", "Maria Antony Dhivyan", "" ] ]
Bacteria produce a range of proteolytic enzymes, for which a number human equivalent or structurally similar examples exist and the primary focus of this study was to analyse the published literature to find proteolytic enzymes, specifically endoproteses and to examine the similarity in the substrates that they act on so as to predict a suitable structural motif which can be used as the basis for preparation of useful prodrug carriers against diseases caused by specific bacteria like Salmonella. Also, the similarities between the bacterial proteases and the action of human matrix metalloproteinases (MMPs), together with the MMP-like activity of bacterial endoproteases to activate human MMPs, were also analysed. This information was used to try to identify substrates on which the MMPs and bacterial proteases act, to aid the design of oligopeptide prodrug carriers to treat cancer and its metastatic spread. MMPs are greatly involved in cancer growth and progression, a few MMPs and certain proteases share a similar type of activity in degrading the extra cellular matrix (ECM) and substrates including gelatin. Our primary targets of study were to identify the proteases and MMPs that facilitate the migration of bacteria and growth of tumour cells respectively. The study was thus a two-way approach to study the substrate specificity of both bacterial proteases and MMPs, thereby to help in characterisation of their substrates. Various bioinformatics tools were used in the characterisation of the proteases and substrates as well as in the identification of possible binding sites and conserved regions in a range of candidate proteins. Central to this project was the salmonella derived PgtE surface protease that has been shown recently to act upon the pro-forms of human MMP-9.
2305.14364
Fani Deligianni Dr
Nicole Lai, Marios Philiastides, Fahim Kawsar, Fani Deligianni
Towards personalised music-therapy; a neurocomputational modelling perspective
null
null
null
null
q-bio.NC cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Music therapy has emerged recently as a successful intervention that improves patient's outcome in a large range of neurological and mood disorders without adverse effects. Brain networks are entrained to music in ways that can be explained both via top-down and bottom-up processes. In particular, the direct interaction of auditory with the motor and the reward system via a predictive framework explains the efficacy of music-based interventions in motor rehabilitation. In this manuscript, we provide a brief overview of current theories of music perception and processing. Subsequently, we summarise evidence of music-based interventions primarily in motor, emotional and cardiovascular regulation. We highlight opportunities to improve quality of life and reduce stress beyond the clinic environment and in healthy individuals. This relatively unexplored area requires an understanding of how we can personalise and automate music selection processes to fit individuals needs and tasks via feedback loops mediated by measurements of neuro-physiological responses.
[ { "created": "Mon, 15 May 2023 19:42:04 GMT", "version": "v1" } ]
2023-05-25
[ [ "Lai", "Nicole", "" ], [ "Philiastides", "Marios", "" ], [ "Kawsar", "Fahim", "" ], [ "Deligianni", "Fani", "" ] ]
Music therapy has emerged recently as a successful intervention that improves patient's outcome in a large range of neurological and mood disorders without adverse effects. Brain networks are entrained to music in ways that can be explained both via top-down and bottom-up processes. In particular, the direct interaction of auditory with the motor and the reward system via a predictive framework explains the efficacy of music-based interventions in motor rehabilitation. In this manuscript, we provide a brief overview of current theories of music perception and processing. Subsequently, we summarise evidence of music-based interventions primarily in motor, emotional and cardiovascular regulation. We highlight opportunities to improve quality of life and reduce stress beyond the clinic environment and in healthy individuals. This relatively unexplored area requires an understanding of how we can personalise and automate music selection processes to fit individuals needs and tasks via feedback loops mediated by measurements of neuro-physiological responses.
2302.01924
Bernd Accou
Bernd Accou, Hugo Van hamme, Tom Francart
CLASH: Contrastive learning through alignment shifting to extract stimulus information from EEG
null
null
null
null
q-bio.NC eess.SP
http://creativecommons.org/licenses/by-nc-nd/4.0/
Stimulus-evoked EEG data has a notoriously low signal-to-noise ratio and high inter-subject variability. We propose a novel paradigm for the self-supervised extraction of stimulus-related brain response data: a model is trained to extract similar information between two time-aligned segments of EEG in response to the same stimulus. The extracted information can subsequently be used to obtain better results in downstream tasks that utilize the response to the stimulus. We show the efficacy of our method for a downstream task of decoding the speech envelope from auditory EEG. Our method outperforms other state-of-the-art denoising techniques, improving reconstruction scores by 45\%. Additionally, we show that in contrast to the baseline denoising techniques, our method can be used with data of unseen subjects and stimuli without retraining, improving decoding performance by 19\% and 34\% over raw EEG for two holdout datasets. Finally, the last experiment reveals that the accuracies obtained in the CLASH paradigm are significantly correlated with the percentile of obtained reconstruction correlation on the null distribution. In general, we showed that the proposed paradigm is suitable to train deep learning models to extract stimulus information from EEG while being stimulus feature agnostic.
[ { "created": "Mon, 9 Jan 2023 13:09:51 GMT", "version": "v1" }, { "created": "Tue, 14 May 2024 11:32:55 GMT", "version": "v2" } ]
2024-05-15
[ [ "Accou", "Bernd", "" ], [ "Van hamme", "Hugo", "" ], [ "Francart", "Tom", "" ] ]
Stimulus-evoked EEG data has a notoriously low signal-to-noise ratio and high inter-subject variability. We propose a novel paradigm for the self-supervised extraction of stimulus-related brain response data: a model is trained to extract similar information between two time-aligned segments of EEG in response to the same stimulus. The extracted information can subsequently be used to obtain better results in downstream tasks that utilize the response to the stimulus. We show the efficacy of our method for a downstream task of decoding the speech envelope from auditory EEG. Our method outperforms other state-of-the-art denoising techniques, improving reconstruction scores by 45\%. Additionally, we show that in contrast to the baseline denoising techniques, our method can be used with data of unseen subjects and stimuli without retraining, improving decoding performance by 19\% and 34\% over raw EEG for two holdout datasets. Finally, the last experiment reveals that the accuracies obtained in the CLASH paradigm are significantly correlated with the percentile of obtained reconstruction correlation on the null distribution. In general, we showed that the proposed paradigm is suitable to train deep learning models to extract stimulus information from EEG while being stimulus feature agnostic.
0712.0973
Martin Depken
Martin Depken, Helmut Schiessel
Nucleosome shape dictates chromatin-fiber structure
13 pages, 3 figures, 1 table, and supporting notes
null
null
null
q-bio.OT
null
Apart from being the gateway for all access to the eukaryotic genome, chromatin has in recent years been identified as carrying an epigenetic code regulating transcriptional activity. The detailed knowledge of this code contrasts the ignorance of the fiber structure which it regulates, and none of the suggested fiber models are capable of predicting the most basic quantities of the fiber (diameter, nucleosome line density, etc.). We address this three-decade-old problem by constructing a simple geometrical model based on the nucleosome shape alone. Without fit parameters we predict the observed properties of the condensed chromatin fiber (e.g. its 30 nm diameter), the structure, and how the fiber changes with varying nucleosome repeat length. Our approach further puts the plethora of previously suggested models within a coherent framework, and opens the door to detailed studies of the interplay between chromatin structure and function.
[ { "created": "Thu, 6 Dec 2007 15:52:33 GMT", "version": "v1" } ]
2007-12-07
[ [ "Depken", "Martin", "" ], [ "Schiessel", "Helmut", "" ] ]
Apart from being the gateway for all access to the eukaryotic genome, chromatin has in recent years been identified as carrying an epigenetic code regulating transcriptional activity. The detailed knowledge of this code contrasts the ignorance of the fiber structure which it regulates, and none of the suggested fiber models are capable of predicting the most basic quantities of the fiber (diameter, nucleosome line density, etc.). We address this three-decade-old problem by constructing a simple geometrical model based on the nucleosome shape alone. Without fit parameters we predict the observed properties of the condensed chromatin fiber (e.g. its 30 nm diameter), the structure, and how the fiber changes with varying nucleosome repeat length. Our approach further puts the plethora of previously suggested models within a coherent framework, and opens the door to detailed studies of the interplay between chromatin structure and function.
1502.05041
Ngoc Hieu Tran
Ngoc Hieu Tran and Xin Chen
AMAS: optimizing the partition and filtration of adaptive seeds to speed up read mapping
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2016
null
10.1109/TCBB.2015.2465900
null
q-bio.GN cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Background: Identifying all possible mapping locations of next-generation sequencing (NGS) reads is highly essential in several applications such as prediction of genomic variants or protein binding motifs located in repeat regions, isoform expression quantification, metagenomics analysis, etc. However, this task is very time-consuming and majority of mapping tools only focus on one or a few best mapping locations. Results: We propose AMAS, an alignment tool specialized in identifying all possible mapping locations of NGS reads in a reference sequence. AMAS features an effective use of adaptive seeds to speed up read mapping while preserving sensitivity. Specifically, an index is designed to pre-store the locations of adaptive seeds in the reference sequence, efficiently reducing the time for seed matching and partitioning. An accurate filtration of adaptive seeds is further applied to substantially tighten the candidate alignment space. As a result, AMAS runs several times faster than other state-of-the-art read mappers while achieving similar accuracy. Conclusions: AMAS provides a valuable resource to speed up the important yet time-consuming task of identifying all mapping locations of NGS reads. AMAS is implemented in C++ based on the SeqAn library and is freely available at https://sourceforge.net/projects/ngsamas/. Keywords: next-generation sequencing, read mapping, sequence alignment, adaptive seeds, seed partition, filtration
[ { "created": "Wed, 18 Feb 2015 02:59:08 GMT", "version": "v1" } ]
2020-03-25
[ [ "Tran", "Ngoc Hieu", "" ], [ "Chen", "Xin", "" ] ]
Background: Identifying all possible mapping locations of next-generation sequencing (NGS) reads is highly essential in several applications such as prediction of genomic variants or protein binding motifs located in repeat regions, isoform expression quantification, metagenomics analysis, etc. However, this task is very time-consuming and majority of mapping tools only focus on one or a few best mapping locations. Results: We propose AMAS, an alignment tool specialized in identifying all possible mapping locations of NGS reads in a reference sequence. AMAS features an effective use of adaptive seeds to speed up read mapping while preserving sensitivity. Specifically, an index is designed to pre-store the locations of adaptive seeds in the reference sequence, efficiently reducing the time for seed matching and partitioning. An accurate filtration of adaptive seeds is further applied to substantially tighten the candidate alignment space. As a result, AMAS runs several times faster than other state-of-the-art read mappers while achieving similar accuracy. Conclusions: AMAS provides a valuable resource to speed up the important yet time-consuming task of identifying all mapping locations of NGS reads. AMAS is implemented in C++ based on the SeqAn library and is freely available at https://sourceforge.net/projects/ngsamas/. Keywords: next-generation sequencing, read mapping, sequence alignment, adaptive seeds, seed partition, filtration
1410.5099
Shubhanshu Shekhar
Shubhanshu Shekhar, Kaushik Majumdar
Identifying features in spike trains using binless similarity measures
19 pages, 4 figures
null
null
null
q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neurons in the central nervous system communicate with each other with the help of series of Action Potentials, or spike trains. Various studies have shown that neurons encode information in different features of spike trains, such as the fine temporal structure, mean firing rate, synchrony etc. An important step in understanding the encoding of information by neurons, is to obtain a reliable measure of correlation between different spike trains. In this paper, two new binless similarity measures for spike trains are proposed. The performance of the new measures are compared with some existing measures in their ability to detect important features of spike trains, such as their firing rate, sensitivity to bursts and common periods of silence and detecting synchronous activity.
[ { "created": "Sun, 19 Oct 2014 17:50:43 GMT", "version": "v1" } ]
2014-10-21
[ [ "Shekhar", "Shubhanshu", "" ], [ "Majumdar", "Kaushik", "" ] ]
Neurons in the central nervous system communicate with each other with the help of series of Action Potentials, or spike trains. Various studies have shown that neurons encode information in different features of spike trains, such as the fine temporal structure, mean firing rate, synchrony etc. An important step in understanding the encoding of information by neurons, is to obtain a reliable measure of correlation between different spike trains. In this paper, two new binless similarity measures for spike trains are proposed. The performance of the new measures are compared with some existing measures in their ability to detect important features of spike trains, such as their firing rate, sensitivity to bursts and common periods of silence and detecting synchronous activity.
2011.05320
Jean-Fran\c{c}ois Cornet
Jean-Fran\c{c}ois Cornet and Claude-Gilles Dussap
A Simple and Reliable Formula for Assessment of Maximum Volumetric Productivities in Photobioreactors
null
Biotechnology Progress, 25, 2009, 424-435
10.1002/btpr.138
null
q-bio.OT physics.bio-ph physics.chem-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper establishes and discusses the consistency and the range of applicability of a simple, but general and predictive analytical formula, enabling to easily assess the maximum volumetric biomass growth rates (the productivities) in several kinds of photobioreactors with more or less 15 percents of deviation. Experimental validations are performed on photobioreactors of very different conceptions and designs, cultivating the cyanobacterium Arthrospira platensis, on a wide range of volumes and hemispherical incident light fluxes. The practical usefulness of the proposed formula is demonstrated by the fact that it appears completely independent of the characteristics of the material phase (as the type of reactor, the kind of mixing, the biomass concentration), according to the first principle of thermodynamics and to the Gauss-Ostrogradsky theorem. Its ability to give the maximum (only) kinetic performance of photobioreactors cultivating many different photoautotrophic strains (cyanobacteria, green algae, eukaryotic microalgae) is theoretically discussed but experimental results are reported to a future work of the authors or to any other contribution arising from the scientific community working in the field of photobioreactor engineering and potentially interested by this approach.
[ { "created": "Sat, 7 Nov 2020 14:39:26 GMT", "version": "v1" } ]
2020-11-11
[ [ "Cornet", "Jean-François", "" ], [ "Dussap", "Claude-Gilles", "" ] ]
This paper establishes and discusses the consistency and the range of applicability of a simple, but general and predictive analytical formula, enabling to easily assess the maximum volumetric biomass growth rates (the productivities) in several kinds of photobioreactors with more or less 15 percents of deviation. Experimental validations are performed on photobioreactors of very different conceptions and designs, cultivating the cyanobacterium Arthrospira platensis, on a wide range of volumes and hemispherical incident light fluxes. The practical usefulness of the proposed formula is demonstrated by the fact that it appears completely independent of the characteristics of the material phase (as the type of reactor, the kind of mixing, the biomass concentration), according to the first principle of thermodynamics and to the Gauss-Ostrogradsky theorem. Its ability to give the maximum (only) kinetic performance of photobioreactors cultivating many different photoautotrophic strains (cyanobacteria, green algae, eukaryotic microalgae) is theoretically discussed but experimental results are reported to a future work of the authors or to any other contribution arising from the scientific community working in the field of photobioreactor engineering and potentially interested by this approach.
2104.00548
Mar\'ia Vallet-Regi
I. Izquierdo-Barba, L. Santos-Ruiz, J. Becerra, M.J. Feito, D. Fernandez-Villa, M.C. Serrano, I. Diaz-Guemes, B. Fernandez-Tome, S. Enciso, F.M. Sanchez Margallo, D. Monopoli, H. Afonso, M.T. Portoles, D. Arcos, M. Vallet-Regi
Synergistic effect of Si-hydroxyapatite coating and VEGF adsorption on Ti6Al4V-ELI scaffolds for bone regeneration in an osteoporotic bone environment
39 pages, 8 figures
Acta Biomaterialia. 83, 456-466 (2018)
10.1016/j.actbio.2018.11.017
null
q-bio.TO
http://creativecommons.org/licenses/by-nc-nd/4.0/
The osteogenic and angiogenic responses to metal macroporous scaffolds coated with silicon substituted hydroxyapatite (SiHA) and decorated with vascular endothelial growth factor (VEGF) have been evaluated in vitro and in vivo. Ti6Al4V-ELI scaffolds were prepared by electron beam melting and subsequently coated with Ca10(PO4)5.6(SiO4)0.4(OH)1.6 following a dip coating method. In vitro studies demonstrated that SiHA stimulates the proliferation of MC3T3-E1 pre-osteoblastic cells, whereas the adsorption of VEGF stimulates the proliferation of EC2 mature endothelial cells. In vivo studies were carried out in an osteoporotic sheep model, evidencing that only the simultaneous presence of both components led to a significant increase of new tissue formation in osteoporotic bone.
[ { "created": "Wed, 10 Mar 2021 11:53:31 GMT", "version": "v1" } ]
2021-04-02
[ [ "Izquierdo-Barba", "I.", "" ], [ "Santos-Ruiz", "L.", "" ], [ "Becerra", "J.", "" ], [ "Feito", "M. J.", "" ], [ "Fernandez-Villa", "D.", "" ], [ "Serrano", "M. C.", "" ], [ "Diaz-Guemes", "I.", "" ], [ "Fernandez-Tome", "B.", "" ], [ "Enciso", "S.", "" ], [ "Margallo", "F. M. Sanchez", "" ], [ "Monopoli", "D.", "" ], [ "Afonso", "H.", "" ], [ "Portoles", "M. T.", "" ], [ "Arcos", "D.", "" ], [ "Vallet-Regi", "M.", "" ] ]
The osteogenic and angiogenic responses to metal macroporous scaffolds coated with silicon substituted hydroxyapatite (SiHA) and decorated with vascular endothelial growth factor (VEGF) have been evaluated in vitro and in vivo. Ti6Al4V-ELI scaffolds were prepared by electron beam melting and subsequently coated with Ca10(PO4)5.6(SiO4)0.4(OH)1.6 following a dip coating method. In vitro studies demonstrated that SiHA stimulates the proliferation of MC3T3-E1 pre-osteoblastic cells, whereas the adsorption of VEGF stimulates the proliferation of EC2 mature endothelial cells. In vivo studies were carried out in an osteoporotic sheep model, evidencing that only the simultaneous presence of both components led to a significant increase of new tissue formation in osteoporotic bone.
2004.06821
Ariel Cintron-Arias
Ariel Cintr\'on-Arias, Fabio S\'anchez, Xiaohong Wang, Carlos Castillo-Chavez, Dennis M. Gorman, Paul J. Gruenewald
The Role of Nonlinear Relapse on Contagion Amongst Drinking Communities
null
null
null
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Relapse, the recurrence of a disorder following a symptomatic remission, is a frequent outcome in substance abuse disorders. Some of our prior results suggested that relapse, in the context of abusive drinking, is likely an "unbeatable" force as long as recovered individuals continue to interact in the environments that lead to and/or reinforce the persistence of abusive drinking behaviors. Our earlier results were obtained via a deterministic model that ignored differences between individuals, that is, in a rather simple "social" setting. In this paper, we address the role of relapse on drinking dynamics but use models that incorporate the role of "chance", or a high degree of "social" heterogeneity, or both. Our focus is primarily on situations where relapse rates are high. We first use a Markov chain model to simulate the effect of relapse on drinking dynamics. These simulations reinforce the conclusions obtained before, with the usual caveats that arise when the outcomes of deterministic and stochastic models are compared. However, the simulation results generated from stochastic realizations of an "equivalent" drinking process in populations "living" in small world networks, parameterized via a disorder parameter $p$, show that there is no social structure within this family capable of reducing the impact of high relapse rates on drinking prevalence, even if we drastically limit the interactions between individuals ($p\approx 0$).
[ { "created": "Tue, 14 Apr 2020 22:30:00 GMT", "version": "v1" } ]
2020-04-16
[ [ "Cintrón-Arias", "Ariel", "" ], [ "Sánchez", "Fabio", "" ], [ "Wang", "Xiaohong", "" ], [ "Castillo-Chavez", "Carlos", "" ], [ "Gorman", "Dennis M.", "" ], [ "Gruenewald", "Paul J.", "" ] ]
Relapse, the recurrence of a disorder following a symptomatic remission, is a frequent outcome in substance abuse disorders. Some of our prior results suggested that relapse, in the context of abusive drinking, is likely an "unbeatable" force as long as recovered individuals continue to interact in the environments that lead to and/or reinforce the persistence of abusive drinking behaviors. Our earlier results were obtained via a deterministic model that ignored differences between individuals, that is, in a rather simple "social" setting. In this paper, we address the role of relapse on drinking dynamics but use models that incorporate the role of "chance", or a high degree of "social" heterogeneity, or both. Our focus is primarily on situations where relapse rates are high. We first use a Markov chain model to simulate the effect of relapse on drinking dynamics. These simulations reinforce the conclusions obtained before, with the usual caveats that arise when the outcomes of deterministic and stochastic models are compared. However, the simulation results generated from stochastic realizations of an "equivalent" drinking process in populations "living" in small world networks, parameterized via a disorder parameter $p$, show that there is no social structure within this family capable of reducing the impact of high relapse rates on drinking prevalence, even if we drastically limit the interactions between individuals ($p\approx 0$).
1606.05006
Jean Vettel PhD
Jean M. Vettel, Justin Kantner, Matthew Jaswa, Michael Miller
Animated 3D Human Models for Use in Person Recognition Experiments
In revision from BRM
null
null
null
q-bio.NC cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The development of increasingly realistic experimental stimuli and task environments is important for understanding behavior outside the laboratory. We report a process for generating 3D human model stimuli that combines commonly used graphics software and enables the flexible generation of animated human models while providing parametric control over individualized identity features. Our approach creates novel head models using FaceGen Modeller, attaches them to commercially-purchased 3D avatar bodies in 3D Studio Max, and generates Cal3D human models that are compatible with many virtual 3D environments. Stimuli produced by this method can be embedded as animated 3D avatars in interactive simulations or presented as 2D images embedded in scenes for use in traditional laboratory experiments. The inherent flexibility in this method makes the stimuli applicable to a broad range of basic and applied research questions in the domain of person perception. We describe the steps of the stimulus generation process, provide an example of their use in a recognition memory paradigm, and highlight the adaptability of the method for related avenues of research.
[ { "created": "Wed, 15 Jun 2016 23:43:53 GMT", "version": "v1" } ]
2016-06-17
[ [ "Vettel", "Jean M.", "" ], [ "Kantner", "Justin", "" ], [ "Jaswa", "Matthew", "" ], [ "Miller", "Michael", "" ] ]
The development of increasingly realistic experimental stimuli and task environments is important for understanding behavior outside the laboratory. We report a process for generating 3D human model stimuli that combines commonly used graphics software and enables the flexible generation of animated human models while providing parametric control over individualized identity features. Our approach creates novel head models using FaceGen Modeller, attaches them to commercially-purchased 3D avatar bodies in 3D Studio Max, and generates Cal3D human models that are compatible with many virtual 3D environments. Stimuli produced by this method can be embedded as animated 3D avatars in interactive simulations or presented as 2D images embedded in scenes for use in traditional laboratory experiments. The inherent flexibility in this method makes the stimuli applicable to a broad range of basic and applied research questions in the domain of person perception. We describe the steps of the stimulus generation process, provide an example of their use in a recognition memory paradigm, and highlight the adaptability of the method for related avenues of research.
2005.03974
Luis R. T. Neves
Luis R. T. Neves and Leonardo Paulo Maia
A simple individual-based population growth model with limited resources
11 pages, 7 figures
null
10.1016/j.physa.2020.125721
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We address a novel approach for stochastic individual-based modelling of a single species population. Individuals are distinguished by their remaining lifetimes, which are regulated by the interplay between the inexorable running of time and the individual's nourishment history. A food-limited environment induces intraspecific competition and henceforth the carrying capacity of the medium may be finite, often emulating the qualitative features of logistic growth. Inherently non-logistic behavior is also obtained by suitable change of the few parameters involved, composing a wide variety of dynamical features. Some analytical results are obtained. Beyond the rich phenomenology observed, we expect that possible modifications of our model may account for an even broader scope of collective population growth phenomena.
[ { "created": "Fri, 8 May 2020 12:08:07 GMT", "version": "v1" }, { "created": "Mon, 8 Jun 2020 22:21:06 GMT", "version": "v2" }, { "created": "Mon, 30 Nov 2020 21:43:46 GMT", "version": "v3" } ]
2021-01-08
[ [ "Neves", "Luis R. T.", "" ], [ "Maia", "Leonardo Paulo", "" ] ]
We address a novel approach for stochastic individual-based modelling of a single species population. Individuals are distinguished by their remaining lifetimes, which are regulated by the interplay between the inexorable running of time and the individual's nourishment history. A food-limited environment induces intraspecific competition and henceforth the carrying capacity of the medium may be finite, often emulating the qualitative features of logistic growth. Inherently non-logistic behavior is also obtained by suitable change of the few parameters involved, composing a wide variety of dynamical features. Some analytical results are obtained. Beyond the rich phenomenology observed, we expect that possible modifications of our model may account for an even broader scope of collective population growth phenomena.
0807.2698
Kilho Eom
Gwonchan Yoon, Hyung-Jin Park, Sungsoo Na, Kilho Eom
Mesoscopic model for mechanical characterization of biological protein materials
29 pages; 7 figures; accepted for publication at Journal of Computational Chemistry
null
null
null
q-bio.BM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mechanical characterization of protein molecules has played a role on gaining insight into the biological functions of proteins, since some proteins perform the mechanical function. Here, we present the mesoscopic model of biological protein materials composed of protein crystals prescribed by Go potential for characterization of elastic behavior of protein materials. Specifically, we consider the representative volume element (RVE) containing the protein crystals represented by alpha-carbon atoms, prescribed by Go potential, with application of constant normal strain to RVE. The stress-strain relationship computed from virial stress theory provides the nonlinear elastic behavior of protein materials and their mechanical properties such as Young's modulus, quantitatively and/or qualitatively comparable to mechanical properties of biological protein materials obtained from experiments and/or atomistic simulations. Further, we discuss the role of native topology on the mechanical properties of protein crystals. It is shown that parallel strands (hydrogen bonds in parallel) enhances the mechanical resilience of protein materials.
[ { "created": "Thu, 17 Jul 2008 05:34:15 GMT", "version": "v1" } ]
2008-07-18
[ [ "Yoon", "Gwonchan", "" ], [ "Park", "Hyung-Jin", "" ], [ "Na", "Sungsoo", "" ], [ "Eom", "Kilho", "" ] ]
Mechanical characterization of protein molecules has played a role on gaining insight into the biological functions of proteins, since some proteins perform the mechanical function. Here, we present the mesoscopic model of biological protein materials composed of protein crystals prescribed by Go potential for characterization of elastic behavior of protein materials. Specifically, we consider the representative volume element (RVE) containing the protein crystals represented by alpha-carbon atoms, prescribed by Go potential, with application of constant normal strain to RVE. The stress-strain relationship computed from virial stress theory provides the nonlinear elastic behavior of protein materials and their mechanical properties such as Young's modulus, quantitatively and/or qualitatively comparable to mechanical properties of biological protein materials obtained from experiments and/or atomistic simulations. Further, we discuss the role of native topology on the mechanical properties of protein crystals. It is shown that parallel strands (hydrogen bonds in parallel) enhances the mechanical resilience of protein materials.
1406.3089
Fernando Antoneli Jr
Guilherme C.P. Innocentini, Michael Forger, Ovidiu Radulescu and Fernando Antoneli
Protein synthesis driven by dynamical stochastic transcription
20 pages, 3 figures
Bulletin of Mathematical Biology, January 2016, Volume 78, Issue 1, pp 110-131
10.1007/s11538-015-0131-3
null
q-bio.SC math.PR physics.bio-ph stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this manuscript we propose a mathematical framework to couple transcription and translation in which mRNA production is described by a set of master equations while the dynamics of protein density is governed by a random differential equation. The coupling between the two processes is given by a stochastic perturbation whose statistics satisfies the master equations. In this approach, from the knowledge of the analytical time dependent distribution of mRNA number, we are able to calculate the dynamics of the probability density of the protein population.
[ { "created": "Thu, 12 Jun 2014 00:34:05 GMT", "version": "v1" }, { "created": "Tue, 23 Dec 2014 15:40:45 GMT", "version": "v2" }, { "created": "Thu, 23 Jul 2015 17:48:17 GMT", "version": "v3" } ]
2020-07-30
[ [ "Innocentini", "Guilherme C. P.", "" ], [ "Forger", "Michael", "" ], [ "Radulescu", "Ovidiu", "" ], [ "Antoneli", "Fernando", "" ] ]
In this manuscript we propose a mathematical framework to couple transcription and translation in which mRNA production is described by a set of master equations while the dynamics of protein density is governed by a random differential equation. The coupling between the two processes is given by a stochastic perturbation whose statistics satisfies the master equations. In this approach, from the knowledge of the analytical time dependent distribution of mRNA number, we are able to calculate the dynamics of the probability density of the protein population.
q-bio/0604017
Philippe Veber
Philippe Veber and Michel Le_Borgne and Anne Siegel and Sandrine Lagarrigue and Ovidiu Radulescu
Complex Qualitative Models in Biology: a new approach
15 pages, 2 figures, ECCS'05, to appear in Complexus
null
null
null
q-bio.MN
null
We advocate the use of qualitative models in the analysis of large biological systems. We show how qualitative models are linked to theoretical differential models and practical graphical models of biological networks. A new technique for analyzing qualitative models is introduced, which is based on an efficient representation of qualitative systems. As shown through several applications, this representation is a relevant tool for the understanding and testing of large and complex biological networks.
[ { "created": "Thu, 13 Apr 2006 15:17:09 GMT", "version": "v1" } ]
2007-05-23
[ [ "Veber", "Philippe", "" ], [ "Le_Borgne", "Michel", "" ], [ "Siegel", "Anne", "" ], [ "Lagarrigue", "Sandrine", "" ], [ "Radulescu", "Ovidiu", "" ] ]
We advocate the use of qualitative models in the analysis of large biological systems. We show how qualitative models are linked to theoretical differential models and practical graphical models of biological networks. A new technique for analyzing qualitative models is introduced, which is based on an efficient representation of qualitative systems. As shown through several applications, this representation is a relevant tool for the understanding and testing of large and complex biological networks.
1702.04873
Jason Olejarz
Jason Olejarz, Carl Veller, Martin A. Nowak
The evolution of queen control over worker reproduction in the social Hymenoptera
null
null
null
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A trademark of eusocial insect species is reproductive division of labor, in which workers forego their own reproduction while the queen produces almost all offspring. The presence of the queen is key for maintaining social harmony, but the specific role of the queen in the evolution of eusociality remains unclear. A long-discussed scenario is that a queen either behaviorally or chemically sterilizes her workers. However, the demographic and ecological conditions that enable such manipulation are unknown. Accordingly, we propose a simple model of evolutionary dynamics that is based on haplodiploid genetics. We consider a mutation that acts in a queen, causing her to control the reproductive behavior of her workers. Our mathematical analysis yields precise conditions for the evolutionary emergence and stability of queen-induced worker sterility. These conditions do not depend on the queen's mating frequency. Moreover, we find that queen control is always established if it increases colony reproductive efficiency and can evolve even if it decreases colony efficiency. We further outline the conditions under which queen control is evolutionarily stable against invasion by mutant, reproductive workers.
[ { "created": "Thu, 16 Feb 2017 07:04:01 GMT", "version": "v1" } ]
2017-02-17
[ [ "Olejarz", "Jason", "" ], [ "Veller", "Carl", "" ], [ "Nowak", "Martin A.", "" ] ]
A trademark of eusocial insect species is reproductive division of labor, in which workers forego their own reproduction while the queen produces almost all offspring. The presence of the queen is key for maintaining social harmony, but the specific role of the queen in the evolution of eusociality remains unclear. A long-discussed scenario is that a queen either behaviorally or chemically sterilizes her workers. However, the demographic and ecological conditions that enable such manipulation are unknown. Accordingly, we propose a simple model of evolutionary dynamics that is based on haplodiploid genetics. We consider a mutation that acts in a queen, causing her to control the reproductive behavior of her workers. Our mathematical analysis yields precise conditions for the evolutionary emergence and stability of queen-induced worker sterility. These conditions do not depend on the queen's mating frequency. Moreover, we find that queen control is always established if it increases colony reproductive efficiency and can evolve even if it decreases colony efficiency. We further outline the conditions under which queen control is evolutionarily stable against invasion by mutant, reproductive workers.
1809.10217
Farshid Jafarpour
Farshid Jafarpour
Cell size regulation induces sustained oscillations in the population growth rate
null
Phys. Rev. Lett. 122, 118101 (2019)
10.1103/PhysRevLett.122.118101
null
q-bio.PE cond-mat.stat-mech physics.bio-ph q-bio.CB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the effect of correlations in generation times on the dynamics of population growth of microorganisms. We show that any non-zero correlation that is due to cell-size regulation, no matter how small, induces long-term oscillations in the population growth rate. The population only reaches its steady state when we include the often-neglected variability in the growth rates of individual cells. We discover that the relaxation time scale of the population to its steady state is determined by the distribution of single-cell growth rates and is surprisingly independent of details of the division process such as the noise in the timing of division and the mechanism of cell-size regulation. We validate the predictions of our model using existing experimental data and propose an experimental method to measure single-cell growth variability by observing how long it takes for the population to reach its steady state or balanced growth.
[ { "created": "Wed, 26 Sep 2018 20:18:19 GMT", "version": "v1" }, { "created": "Mon, 10 Dec 2018 23:14:11 GMT", "version": "v2" } ]
2019-03-27
[ [ "Jafarpour", "Farshid", "" ] ]
We study the effect of correlations in generation times on the dynamics of population growth of microorganisms. We show that any non-zero correlation that is due to cell-size regulation, no matter how small, induces long-term oscillations in the population growth rate. The population only reaches its steady state when we include the often-neglected variability in the growth rates of individual cells. We discover that the relaxation time scale of the population to its steady state is determined by the distribution of single-cell growth rates and is surprisingly independent of details of the division process such as the noise in the timing of division and the mechanism of cell-size regulation. We validate the predictions of our model using existing experimental data and propose an experimental method to measure single-cell growth variability by observing how long it takes for the population to reach its steady state or balanced growth.
1110.4294
Olivier Faugeras
Javier Baladron, Diego Fasoli, Olivier Faugeras and Jonathan Touboul
Mean Field description of and propagation of chaos in recurrent multipopulation networks of Hodgkin-Huxley and Fitzhugh-Nagumo neurons
55 pages, 9 figures
null
null
null
q-bio.NC math.PR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We derive the mean-field equations arising as the limit of a network of interacting spiking neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number of populations and are represented either by the Hodgkin-Huxley model or by one of its simplified version, the Fitzhugh-Nagumo model. The synapses between neurons are either electrical or chemical. The network is assumed to be fully connected. The maximum conductances vary randomly. Under the condition that all neurons initial conditions are drawn independently from the same law that depends only on the population they belong to, we prove that a propagation of chaos phenomenon takes places, namely that in the mean-field limit, any finite number of neurons become independent and, within each population, have the same probability distribution. This probability distribution is solution of a set of implicit equations, either nonlinear stochastic differential equations resembling the McKean-Vlasov equations, or non-local partial differential equations resembling the McKean-Vlasov-Fokker- Planck equations. We prove the well-posedness of these equations, i.e. the existence and uniqueness of a solution. We also show the results of some preliminary numerical experiments that indicate that the mean-field equations are a good representation of the mean activity of a finite size network, even for modest sizes. These experiment also indicate that the McKean-Vlasov-Fokker- Planck equations may be a good way to understand the mean-field dynamics through, e.g., a bifurcation analysis.
[ { "created": "Wed, 19 Oct 2011 14:21:43 GMT", "version": "v1" } ]
2016-11-25
[ [ "Baladron", "Javier", "" ], [ "Fasoli", "Diego", "" ], [ "Faugeras", "Olivier", "" ], [ "Touboul", "Jonathan", "" ] ]
We derive the mean-field equations arising as the limit of a network of interacting spiking neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number of populations and are represented either by the Hodgkin-Huxley model or by one of its simplified version, the Fitzhugh-Nagumo model. The synapses between neurons are either electrical or chemical. The network is assumed to be fully connected. The maximum conductances vary randomly. Under the condition that all neurons initial conditions are drawn independently from the same law that depends only on the population they belong to, we prove that a propagation of chaos phenomenon takes places, namely that in the mean-field limit, any finite number of neurons become independent and, within each population, have the same probability distribution. This probability distribution is solution of a set of implicit equations, either nonlinear stochastic differential equations resembling the McKean-Vlasov equations, or non-local partial differential equations resembling the McKean-Vlasov-Fokker- Planck equations. We prove the well-posedness of these equations, i.e. the existence and uniqueness of a solution. We also show the results of some preliminary numerical experiments that indicate that the mean-field equations are a good representation of the mean activity of a finite size network, even for modest sizes. These experiment also indicate that the McKean-Vlasov-Fokker- Planck equations may be a good way to understand the mean-field dynamics through, e.g., a bifurcation analysis.
1708.07882
Hiroki Sayama
Hyobin Kim and Hiroki Sayama
The Role of Criticality of Gene Regulatory Networks in Morphogenesis
11 pages, 13 figures, 1 table; accepted for publication in IEEE Transactions on Cognitive and Developmental Systems
null
null
null
q-bio.CB nlin.AO nlin.PS physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gene regulatory network (GRN)-based morphogenetic models have recently gained an increasing attention. However, the relationship between microscopic properties of intracellular GRNs and macroscopic properties of morphogenetic systems has not been fully understood yet. Here we propose a theoretical morphogenetic model representing an aggregation of cells, and reveal the relationship between criticality of GRNs and morphogenetic pattern formation. In our model, the positions of the cells are determined by spring-mass-damper kinetics. Each cell has an identical Kauffman's $NK$ random Boolean network (RBN) as its GRN. We varied the properties of GRNs from ordered, through critical, to chaotic by adjusting node in-degree $K$. We randomly assigned four cell fates to the attractors of RBNs for cellular behaviors. By comparing diverse morphologies generated in our morphogenetic systems, we investigated what the role of the criticality of GRNs is in forming morphologies. We found that nontrivial spatial patterns were generated most frequently when GRNs were at criticality. Our finding indicates that the criticality of GRNs facilitates the formation of nontrivial morphologies in GRN-based morphogenetic systems.
[ { "created": "Sat, 12 Aug 2017 18:47:06 GMT", "version": "v1" }, { "created": "Thu, 9 Aug 2018 18:38:21 GMT", "version": "v2" }, { "created": "Wed, 10 Oct 2018 12:33:12 GMT", "version": "v3" } ]
2018-10-11
[ [ "Kim", "Hyobin", "" ], [ "Sayama", "Hiroki", "" ] ]
Gene regulatory network (GRN)-based morphogenetic models have recently gained an increasing attention. However, the relationship between microscopic properties of intracellular GRNs and macroscopic properties of morphogenetic systems has not been fully understood yet. Here we propose a theoretical morphogenetic model representing an aggregation of cells, and reveal the relationship between criticality of GRNs and morphogenetic pattern formation. In our model, the positions of the cells are determined by spring-mass-damper kinetics. Each cell has an identical Kauffman's $NK$ random Boolean network (RBN) as its GRN. We varied the properties of GRNs from ordered, through critical, to chaotic by adjusting node in-degree $K$. We randomly assigned four cell fates to the attractors of RBNs for cellular behaviors. By comparing diverse morphologies generated in our morphogenetic systems, we investigated what the role of the criticality of GRNs is in forming morphologies. We found that nontrivial spatial patterns were generated most frequently when GRNs were at criticality. Our finding indicates that the criticality of GRNs facilitates the formation of nontrivial morphologies in GRN-based morphogenetic systems.
0812.1062
Anthony Norcia
Richard T. Miller, Vladimir Y. Vildavski, Anthony M. Norcia
Improved Volterra Kernel Methods with Applications to the Visual System
null
null
null
null
q-bio.QM q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Volterra analysis and its variants have long been prominent among methods for modeling multi-input non-linear systems. The product of Volterra analysis, the Volterra kernels, are particularly suited to quantifying intra- and inter-input interactions. They are also readily interpretable, which means that they can be related directly to physical behaviors, and more distantly, to the underlying processing mechanisms of the system being tested. However, accurate estimation of a sufficient set of classical kernels is often not possible for complex systems because the number of kernels that need to be determined, and hence experiment time, increases radically with system memory, response frequency bandwidth, and non-linear interaction order. Practical approaches to kernel estimation often involve forced reductions of the generality of the analysis that in turn compromise interpretability. Here we illustrate the effects on kernel interpretability of two common reductions, slow-stimulation and the use of binary inputs, using both numerical simulations and data from a Visual Evoked Potential experiment. We show how a non-standard version of binary analysis, involving a different coding of the inputs and the use of particular groupings of kernel slices, improves kernel interpretability. We bring together, in a comprehensive fashion, all of the mathematical considerations needed to apply and interpret the results of Volterra kernel analyses. The input-coding method we describe allows one to correctly quantify multi-input interactive effects that occur both within the separate input channels and across them.
[ { "created": "Fri, 5 Dec 2008 00:20:09 GMT", "version": "v1" } ]
2008-12-08
[ [ "Miller", "Richard T.", "" ], [ "Vildavski", "Vladimir Y.", "" ], [ "Norcia", "Anthony M.", "" ] ]
Volterra analysis and its variants have long been prominent among methods for modeling multi-input non-linear systems. The product of Volterra analysis, the Volterra kernels, are particularly suited to quantifying intra- and inter-input interactions. They are also readily interpretable, which means that they can be related directly to physical behaviors, and more distantly, to the underlying processing mechanisms of the system being tested. However, accurate estimation of a sufficient set of classical kernels is often not possible for complex systems because the number of kernels that need to be determined, and hence experiment time, increases radically with system memory, response frequency bandwidth, and non-linear interaction order. Practical approaches to kernel estimation often involve forced reductions of the generality of the analysis that in turn compromise interpretability. Here we illustrate the effects on kernel interpretability of two common reductions, slow-stimulation and the use of binary inputs, using both numerical simulations and data from a Visual Evoked Potential experiment. We show how a non-standard version of binary analysis, involving a different coding of the inputs and the use of particular groupings of kernel slices, improves kernel interpretability. We bring together, in a comprehensive fashion, all of the mathematical considerations needed to apply and interpret the results of Volterra kernel analyses. The input-coding method we describe allows one to correctly quantify multi-input interactive effects that occur both within the separate input channels and across them.
2106.12823
Somya Mehra
Somya Mehra, James M. McCaw, Mark B. Flegg, Peter G. Taylor, Jennifer A. Flegg
An activation-clearance model for Plasmodium vivax malaria
This is a pre-copyedit version of an article published in Bulletin of Mathematical Biology. The final authenticated version is available online at: https://doi.org/10.1007/s11538-020-00706-1
Bull Math Biol 82, 32 (2020)
10.1007/s11538-020-00706-1
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Malaria is an infectious disease with an immense global health burden. Plasmodium vivax is the most geographically widespread species of malaria. Relapsing infections, caused by the activation of liver-stage parasites known as hypnozoites, are a critical feature of the epidemiology of Plasmodium vivax. Hypnozoites remain dormant in the liver for weeks or months after inoculation, but cause relapsing infections upon activation. Here, we introduce a dynamic probability model of the activation-clearance process governing both potential relapses and the size of the hypnozoite reservoir. We begin by modelling activation-clearance dynamics for a single hypnozoite using a continuous-time Markov chain. We then extend our analysis to consider activation-clearance dynamics for a single mosquito bite, which can simultaneously establish multiple hypnozoites, under the assumption of independent hypnozoite behaviour. We derive analytic expressions for the time to first relapse and the time to hypnozoite clearance for mosquito bites establishing variable numbers of hypnozoites, both of which are quantities of epidemiological significance. Our results extend those in the literature, which were limited due to an assumption of non-independence. Our within-host model can be embedded readily in multi-scale models and epidemiological frameworks, with analytic solutions increasing the tractability of statistical inference and analysis. Our work therefore provides a foundation for further work on immune development and epidemiological-scale analysis, both of which are important for achieving the goal of malaria elimination.
[ { "created": "Thu, 24 Jun 2021 08:22:04 GMT", "version": "v1" } ]
2021-06-25
[ [ "Mehra", "Somya", "" ], [ "McCaw", "James M.", "" ], [ "Flegg", "Mark B.", "" ], [ "Taylor", "Peter G.", "" ], [ "Flegg", "Jennifer A.", "" ] ]
Malaria is an infectious disease with an immense global health burden. Plasmodium vivax is the most geographically widespread species of malaria. Relapsing infections, caused by the activation of liver-stage parasites known as hypnozoites, are a critical feature of the epidemiology of Plasmodium vivax. Hypnozoites remain dormant in the liver for weeks or months after inoculation, but cause relapsing infections upon activation. Here, we introduce a dynamic probability model of the activation-clearance process governing both potential relapses and the size of the hypnozoite reservoir. We begin by modelling activation-clearance dynamics for a single hypnozoite using a continuous-time Markov chain. We then extend our analysis to consider activation-clearance dynamics for a single mosquito bite, which can simultaneously establish multiple hypnozoites, under the assumption of independent hypnozoite behaviour. We derive analytic expressions for the time to first relapse and the time to hypnozoite clearance for mosquito bites establishing variable numbers of hypnozoites, both of which are quantities of epidemiological significance. Our results extend those in the literature, which were limited due to an assumption of non-independence. Our within-host model can be embedded readily in multi-scale models and epidemiological frameworks, with analytic solutions increasing the tractability of statistical inference and analysis. Our work therefore provides a foundation for further work on immune development and epidemiological-scale analysis, both of which are important for achieving the goal of malaria elimination.
0903.5178
Francois J. Nedelec
Francois Nedelec and Dietrich Foethke
Collective Langevin Dynamics of Flexible Cytoskeletal Fibers
27 pages, 10 figures
Francois Nedelec et al 2007 New J. Phys. 9 427
10.1088/1367-2630/9/11/427
null
q-bio.CB q-bio.SC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We develop a numerical method to simulate mechanical objects in a viscous medium at a scale where inertia is negligible. Fibers, spheres and other voluminous objects are represented with points. Different types of connections are used to link the points together and in this way create composite mechanical structures. The motion of such structures in a Brownian environment is described by a first-order multivariate Langevin equation. We propose a computationally efficient method to integrate the equation, and illustrate the applicability of the method to cytoskeletal modeling with several examples.
[ { "created": "Mon, 30 Mar 2009 10:50:47 GMT", "version": "v1" } ]
2009-03-31
[ [ "Nedelec", "Francois", "" ], [ "Foethke", "Dietrich", "" ] ]
We develop a numerical method to simulate mechanical objects in a viscous medium at a scale where inertia is negligible. Fibers, spheres and other voluminous objects are represented with points. Different types of connections are used to link the points together and in this way create composite mechanical structures. The motion of such structures in a Brownian environment is described by a first-order multivariate Langevin equation. We propose a computationally efficient method to integrate the equation, and illustrate the applicability of the method to cytoskeletal modeling with several examples.
2012.05950
Ryan Blything
Ryan Blything, Valerio Biscione, Jeffrey Bowers
A case for robust translation tolerance in humans and CNNs. A commentary on Han et al
8 pages, 3 figures
null
null
null
q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Han et al. (2020) reported a behavioral experiment that assessed the extent to which the human visual system can identify novel images at unseen retinal locations (what the authors call "intrinsic translation invariance") and developed a novel convolutional neural network model (an Eccentricity Dependent Network or ENN) to capture key aspects of the behavioral results. Here we show that their analysis of behavioral data used inappropriate baseline conditions, leading them to underestimate intrinsic translation invariance. When the data are correctly interpreted they show near complete translation tolerance extending to 14{\deg} in some conditions, consistent with earlier work (Bowers et al., 2016) and more recent work Blything et al. (in press). We describe a simpler model that provides a better account of translation invariance.
[ { "created": "Thu, 10 Dec 2020 20:12:14 GMT", "version": "v1" }, { "created": "Mon, 14 Dec 2020 14:59:56 GMT", "version": "v2" } ]
2020-12-15
[ [ "Blything", "Ryan", "" ], [ "Biscione", "Valerio", "" ], [ "Bowers", "Jeffrey", "" ] ]
Han et al. (2020) reported a behavioral experiment that assessed the extent to which the human visual system can identify novel images at unseen retinal locations (what the authors call "intrinsic translation invariance") and developed a novel convolutional neural network model (an Eccentricity Dependent Network or ENN) to capture key aspects of the behavioral results. Here we show that their analysis of behavioral data used inappropriate baseline conditions, leading them to underestimate intrinsic translation invariance. When the data are correctly interpreted they show near complete translation tolerance extending to 14{\deg} in some conditions, consistent with earlier work (Bowers et al., 2016) and more recent work Blything et al. (in press). We describe a simpler model that provides a better account of translation invariance.
q-bio/0411016
Wentian Li
Wentian Li, Dirk Holste
Universal 1/f noise, cross-overs of scaling exponents, and chromosome specific patterns of GC content in DNA sequences of the human genome
9 pages (figures included), 9 figures
Physical Review E, 71, 041910 (2005)
10.1103/PhysRevE.71.041910
q-bio.GN/0411016
q-bio.GN q-bio.BM
null
Spatial fluctuations of guanine and cytosine base content (GC%) are studied by spectral analysis for the complete set of human genomic DNA sequences. We find that (i) the 1/f^alpha decay is universally observed in the power spectra of all twenty-four chromosomes, and that (ii) the exponent alpha \approx 1 extends to about 10^7 bases, one order of magnitude longer than what has previously been observed. We further find that (iii) almost all human chromosomes exhibit a cross-over from alpha_1 \approx 1 (1/f^alpha_1) at lower frequency to alpha_2 < 1 (1/f^alpha_2) at higher frequency, typically occurring at around 30,000--100,000 bases, while (iv) the cross-over in this frequency range is virtually absent in human chromosome 22. In addition to the universal 1/f^alpha noise in power spectra, we find (v) several lines of evidence for chromosome-specific correlation structures, including a 500,000 bases long oscillation in human chromosome 21. The universal 1/f^alpha spectrum in human genome is further substantiated by a resistance to variance reduction in guanine and cytosine content when the window size is increased.
[ { "created": "Wed, 3 Nov 2004 21:31:43 GMT", "version": "v1" } ]
2007-05-23
[ [ "Li", "Wentian", "" ], [ "Holste", "Dirk", "" ] ]
Spatial fluctuations of guanine and cytosine base content (GC%) are studied by spectral analysis for the complete set of human genomic DNA sequences. We find that (i) the 1/f^alpha decay is universally observed in the power spectra of all twenty-four chromosomes, and that (ii) the exponent alpha \approx 1 extends to about 10^7 bases, one order of magnitude longer than what has previously been observed. We further find that (iii) almost all human chromosomes exhibit a cross-over from alpha_1 \approx 1 (1/f^alpha_1) at lower frequency to alpha_2 < 1 (1/f^alpha_2) at higher frequency, typically occurring at around 30,000--100,000 bases, while (iv) the cross-over in this frequency range is virtually absent in human chromosome 22. In addition to the universal 1/f^alpha noise in power spectra, we find (v) several lines of evidence for chromosome-specific correlation structures, including a 500,000 bases long oscillation in human chromosome 21. The universal 1/f^alpha spectrum in human genome is further substantiated by a resistance to variance reduction in guanine and cytosine content when the window size is increased.
2201.09471
Mobolaji Williams
Mobolaji Williams
Derangement model of ligand-receptor binding
57 pages, 21 figures
Computational and Mathematical Biophysics 10.1 (2022): 123-166
10.1515/cmb-2022-0137
null
q-bio.BM cond-mat.stat-mech
http://creativecommons.org/licenses/by/4.0/
We introduce a derangement model of ligand-receptor binding that allows us to quantitatively frame the question "How can ligands seek out and bind to their optimal receptor sites in a sea of other competing ligands and suboptimal receptor sites?" To answer the question, we first derive a formula to count the number of partial generalized derangements in a list, thus extending the derangement result of Gillis and Even. We then compute the general partition function for the ligand-receptor system and derive the equilibrium expressions for the average number of bound ligands and the average number of optimally bound ligands. A visual model of squares assembling onto a grid allows us to easily identify fully optimal bound states. Equilibrium simulations of the system reveal its extremes to be one of two types, qualitatively distinguished by whether optimal ligand-receptor binding is the dominant form of binding at all temperatures and quantitatively distinguished by the relative values of two critical temperatures. One of those system types (termed "search-limited," as it was in previous work) does not exhibit kinetic traps and we thus infer that biomolecular systems where optimal ligand-receptor binding is functionally important are likely to be search-limited.
[ { "created": "Mon, 24 Jan 2022 06:04:37 GMT", "version": "v1" }, { "created": "Tue, 23 Aug 2022 01:46:55 GMT", "version": "v2" } ]
2022-08-24
[ [ "Williams", "Mobolaji", "" ] ]
We introduce a derangement model of ligand-receptor binding that allows us to quantitatively frame the question "How can ligands seek out and bind to their optimal receptor sites in a sea of other competing ligands and suboptimal receptor sites?" To answer the question, we first derive a formula to count the number of partial generalized derangements in a list, thus extending the derangement result of Gillis and Even. We then compute the general partition function for the ligand-receptor system and derive the equilibrium expressions for the average number of bound ligands and the average number of optimally bound ligands. A visual model of squares assembling onto a grid allows us to easily identify fully optimal bound states. Equilibrium simulations of the system reveal its extremes to be one of two types, qualitatively distinguished by whether optimal ligand-receptor binding is the dominant form of binding at all temperatures and quantitatively distinguished by the relative values of two critical temperatures. One of those system types (termed "search-limited," as it was in previous work) does not exhibit kinetic traps and we thus infer that biomolecular systems where optimal ligand-receptor binding is functionally important are likely to be search-limited.
1609.00520
Jorge Hidalgo
Jorge Hidalgo, Samir Suweis and Amos Maritan
Species coexistence in a neutral dynamics with environmental noise
11 pages, 4 figures
Journal of Theoretical Biology 413 (2017) 1-10
10.1016/j.jtbi.2016.11.002
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Environmental fluctuations have important consequences in the organization of ecological communities, and understanding how such a variability influences the biodiversity of an ecosystem is a major question in ecology. In this paper, we analyze the case of two species competing for the resources within the framework of the neutral theory in the presence of environmental noise, devoting special attention on how such a variability modulates species fitness. The environment is dichotomous and stochastically alternates between periods favoring one of the species while disfavoring the other one, preserving neutrality on the long term. We study two different scenarios: in the first one species fitness varies linearly with the environment, and in the second one the effective fitness is re-scaled by the total fitness of the individuals competing for the same resource. We find that, in the former case environmental fluctuations always reduce the time of species coexistence, whereas such a time can be enhanced or reduced in the latter case, depending on the correlation time of the environment. This phenomenon can be understood as a direct consequence of Chesson's storage effect.
[ { "created": "Fri, 2 Sep 2016 09:36:31 GMT", "version": "v1" }, { "created": "Tue, 15 Nov 2016 10:21:05 GMT", "version": "v2" } ]
2016-11-16
[ [ "Hidalgo", "Jorge", "" ], [ "Suweis", "Samir", "" ], [ "Maritan", "Amos", "" ] ]
Environmental fluctuations have important consequences in the organization of ecological communities, and understanding how such a variability influences the biodiversity of an ecosystem is a major question in ecology. In this paper, we analyze the case of two species competing for the resources within the framework of the neutral theory in the presence of environmental noise, devoting special attention on how such a variability modulates species fitness. The environment is dichotomous and stochastically alternates between periods favoring one of the species while disfavoring the other one, preserving neutrality on the long term. We study two different scenarios: in the first one species fitness varies linearly with the environment, and in the second one the effective fitness is re-scaled by the total fitness of the individuals competing for the same resource. We find that, in the former case environmental fluctuations always reduce the time of species coexistence, whereas such a time can be enhanced or reduced in the latter case, depending on the correlation time of the environment. This phenomenon can be understood as a direct consequence of Chesson's storage effect.
1007.1315
Jin Yang
Jin Yang, Xin Meng, and William S. Hlavacek
Rule-based Modeling and Simulation of Biochemical Systems with Molecular Finite Automata
23 pages, 6 figures
null
null
null
q-bio.QM q-bio.MN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a theoretical formalism, molecular finite automata (MFA), to describe individual proteins as rule-based computing machines. The MFA formalism provides a framework for modeling individual protein behaviors and systems-level dynamics via construction of programmable and executable machines. Models specified within this formalism explicitly represent the context-sensitive dynamics of individual proteins driven by external inputs and represent protein-protein interactions as synchronized machine reconfigurations. Both deterministic and stochastic simulations can be applied to quantitatively compute the dynamics of MFA models. We apply the MFA formalism to model and simulate a simple example of a signal transduction system that involves a MAP kinase cascade and a scaffold protein.
[ { "created": "Thu, 8 Jul 2010 09:02:14 GMT", "version": "v1" }, { "created": "Wed, 15 Sep 2010 07:52:55 GMT", "version": "v2" } ]
2010-09-16
[ [ "Yang", "Jin", "" ], [ "Meng", "Xin", "" ], [ "Hlavacek", "William S.", "" ] ]
We propose a theoretical formalism, molecular finite automata (MFA), to describe individual proteins as rule-based computing machines. The MFA formalism provides a framework for modeling individual protein behaviors and systems-level dynamics via construction of programmable and executable machines. Models specified within this formalism explicitly represent the context-sensitive dynamics of individual proteins driven by external inputs and represent protein-protein interactions as synchronized machine reconfigurations. Both deterministic and stochastic simulations can be applied to quantitatively compute the dynamics of MFA models. We apply the MFA formalism to model and simulate a simple example of a signal transduction system that involves a MAP kinase cascade and a scaffold protein.
1611.01682
Andrew D. Rutenberg
Spencer Farrell, Arnold Mitnitski, Kenneth Rockwood, Andrew Rutenberg
Network model of human aging: frailty limits and information measures
12 pages
Physical Review E, v 94, 052409 (2016)
10.1103/PhysRevE.94.052409
null
q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Aging is associated with the accumulation of damage throughout a persons life. Individual health can be assessed by the Frailty Index (FI). The FI is calculated simply as the proportion $f$ of accumulated age related deficits relative to the total, leading to a theoretical maximum of $f \leq 1$. Observational studies have generally reported a much more stringent bound, with $f \leq f_{max} <1$. The value of $f_{max}$ in observational studies appears to be non-universal, but $f_{max} \approx 0.7$ is often reported. A previously developed network model of individual aging was unable to recover $f_{max}<1$ while retaining the other observed phenomenology of increasing $f$ and mortality rates with age. We have developed a computationally accelerated network model that also allows us to tune the scale-free network exponent $\alpha$. The network exponent $\alpha$ significantly affects the growth of mortality rates with age. However, we are only able to recover $f_{max}$ by also introducing a deficit sensitivity parameter $1-q$, which is equivalent to a false-negative rate $q$. Our value of $q=0.3$ is comparable to finite sensitivities of age-related deficits with respect to mortality that are often reported in the literature. In light of non-zero $q$, we use mutual information $I$ to provide a non-parametric measure of the predictive value of the FI with respect to individual mortality. We find that $I$ is only modestly degraded by $q<1$, and this degradation is mitigated when increasing number of deficits are included in the FI. We also find that the information spectrum, i.e. the mutual information of individual deficits vs connectivity, has an approximately power-law dependence that depends on the network exponent $\alpha$. Mutual information $I$ is therefore a useful tool for characterizing the network topology of aging populations.
[ { "created": "Sat, 5 Nov 2016 17:39:26 GMT", "version": "v1" } ]
2023-12-15
[ [ "Farrell", "Spencer", "" ], [ "Mitnitski", "Arnold", "" ], [ "Rockwood", "Kenneth", "" ], [ "Rutenberg", "Andrew", "" ] ]
Aging is associated with the accumulation of damage throughout a persons life. Individual health can be assessed by the Frailty Index (FI). The FI is calculated simply as the proportion $f$ of accumulated age related deficits relative to the total, leading to a theoretical maximum of $f \leq 1$. Observational studies have generally reported a much more stringent bound, with $f \leq f_{max} <1$. The value of $f_{max}$ in observational studies appears to be non-universal, but $f_{max} \approx 0.7$ is often reported. A previously developed network model of individual aging was unable to recover $f_{max}<1$ while retaining the other observed phenomenology of increasing $f$ and mortality rates with age. We have developed a computationally accelerated network model that also allows us to tune the scale-free network exponent $\alpha$. The network exponent $\alpha$ significantly affects the growth of mortality rates with age. However, we are only able to recover $f_{max}$ by also introducing a deficit sensitivity parameter $1-q$, which is equivalent to a false-negative rate $q$. Our value of $q=0.3$ is comparable to finite sensitivities of age-related deficits with respect to mortality that are often reported in the literature. In light of non-zero $q$, we use mutual information $I$ to provide a non-parametric measure of the predictive value of the FI with respect to individual mortality. We find that $I$ is only modestly degraded by $q<1$, and this degradation is mitigated when increasing number of deficits are included in the FI. We also find that the information spectrum, i.e. the mutual information of individual deficits vs connectivity, has an approximately power-law dependence that depends on the network exponent $\alpha$. Mutual information $I$ is therefore a useful tool for characterizing the network topology of aging populations.
2311.08135
Leo Kozachkov
Leo Kozachkov, Jean-Jacques Slotine, Dmitry Krotov
Neuron-Astrocyte Associative Memory
Main text: 14 pages, 3 figures. Appendix: 8 pages, 2 figures
null
null
null
q-bio.NC
http://creativecommons.org/licenses/by/4.0/
Astrocytes, the most abundant type of glial cell, play a fundamental role in memory. Despite most hippocampal synapses being contacted by an astrocyte, there are no current theories that explain how neurons, synapses, and astrocytes might collectively contribute to memory function. We demonstrate that fundamental aspects of astrocyte morphology and physiology naturally lead to a dynamic, high-capacity associative memory system. The neuron-astrocyte networks generated by our framework are closely related to popular machine learning architectures known as Dense Associative Memories or Modern Hopfield Networks. In their known biological implementations the ratio of stored memories to the number of neurons remains constant, despite the growth of the network size. Our work demonstrates that neuron-astrocyte networks follow superior, supralinear memory scaling laws, outperforming all known biological implementations of Dense Associative Memory. This theoretical link suggests the exciting and previously unnoticed possibility that memories could be stored, at least in part, within astrocytes rather than solely in the synaptic weights between neurons.
[ { "created": "Tue, 14 Nov 2023 13:01:50 GMT", "version": "v1" }, { "created": "Tue, 23 Jul 2024 00:50:51 GMT", "version": "v2" } ]
2024-07-24
[ [ "Kozachkov", "Leo", "" ], [ "Slotine", "Jean-Jacques", "" ], [ "Krotov", "Dmitry", "" ] ]
Astrocytes, the most abundant type of glial cell, play a fundamental role in memory. Despite most hippocampal synapses being contacted by an astrocyte, there are no current theories that explain how neurons, synapses, and astrocytes might collectively contribute to memory function. We demonstrate that fundamental aspects of astrocyte morphology and physiology naturally lead to a dynamic, high-capacity associative memory system. The neuron-astrocyte networks generated by our framework are closely related to popular machine learning architectures known as Dense Associative Memories or Modern Hopfield Networks. In their known biological implementations the ratio of stored memories to the number of neurons remains constant, despite the growth of the network size. Our work demonstrates that neuron-astrocyte networks follow superior, supralinear memory scaling laws, outperforming all known biological implementations of Dense Associative Memory. This theoretical link suggests the exciting and previously unnoticed possibility that memories could be stored, at least in part, within astrocytes rather than solely in the synaptic weights between neurons.
1105.5063
Jose Vilar
Jose M. G. Vilar and Leonor Saiz
Control of gene expression by modulated self-assembly
Nucleic Acids Research, (2011); Published version available at http://nar.oxfordjournals.org/content/early/2011/05/20/nar.gkr272.full
null
10.1093/nar/gkr272
null
q-bio.MN cond-mat.soft physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Numerous transcription factors self-assemble into different order oligomeric species in a way that is actively regulated by the cell. Until now, no general functional role has been identified for this widespread process. Here we capture the effects of modulated self-assembly in gene expression with a novel quantitative framework. We show that this mechanism provides precision and flexibility, two seemingly antagonistic properties, to the sensing of diverse cellular signals by systems that share common elements present in transcription factors like p53, NF-kappaB, STATs, Oct, and RXR. Applied to the nuclear hormone receptor RXR, this framework accurately reproduces a broad range of classical, previously unexplained, sets of gene expression data and corroborates the existence of a precise functional regime with flexible properties that can be controlled both at a genome-wide scale and at the individual promoter level.
[ { "created": "Wed, 25 May 2011 15:26:27 GMT", "version": "v1" } ]
2011-05-26
[ [ "Vilar", "Jose M. G.", "" ], [ "Saiz", "Leonor", "" ] ]
Numerous transcription factors self-assemble into different order oligomeric species in a way that is actively regulated by the cell. Until now, no general functional role has been identified for this widespread process. Here we capture the effects of modulated self-assembly in gene expression with a novel quantitative framework. We show that this mechanism provides precision and flexibility, two seemingly antagonistic properties, to the sensing of diverse cellular signals by systems that share common elements present in transcription factors like p53, NF-kappaB, STATs, Oct, and RXR. Applied to the nuclear hormone receptor RXR, this framework accurately reproduces a broad range of classical, previously unexplained, sets of gene expression data and corroborates the existence of a precise functional regime with flexible properties that can be controlled both at a genome-wide scale and at the individual promoter level.
1506.00054
Justin Kinney
Gurinder S. Atwal and Justin B. Kinney
Learning quantitative sequence-function relationships from massively parallel experiments
35 pages, 8 figures. Revised manuscript currently under review for publication
null
10.1007/s10955-015-1398-3
null
q-bio.QM math.ST physics.bio-ph physics.data-an stat.ML stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships -- functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes" -- directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.
[ { "created": "Sat, 30 May 2015 01:20:59 GMT", "version": "v1" }, { "created": "Tue, 22 Sep 2015 15:47:20 GMT", "version": "v2" } ]
2016-03-23
[ [ "Atwal", "Gurinder S.", "" ], [ "Kinney", "Justin B.", "" ] ]
A fundamental aspect of biological information processing is the ubiquity of sequence-function relationships -- functions that map the sequence of DNA, RNA, or protein to a biochemically relevant activity. Most sequence-function relationships in biology are quantitative, but only recently have experimental techniques for effectively measuring these relationships been developed. The advent of such "massively parallel" experiments presents an exciting opportunity for the concepts and methods of statistical physics to inform the study of biological systems. After reviewing these recent experimental advances, we focus on the problem of how to infer parametric models of sequence-function relationships from the data produced by these experiments. Specifically, we retrace and extend recent theoretical work showing that inference based on mutual information, not the standard likelihood-based approach, is often necessary for accurately learning the parameters of these models. Closely connected with this result is the emergence of "diffeomorphic modes" -- directions in parameter space that are far less constrained by data than likelihood-based inference would suggest. Analogous to Goldstone modes in physics, diffeomorphic modes arise from an arbitrarily broken symmetry of the inference problem. An analytically tractable model of a massively parallel experiment is then described, providing an explicit demonstration of these fundamental aspects of statistical inference. This paper concludes with an outlook on the theoretical and computational challenges currently facing studies of quantitative sequence-function relationships.
2304.03230
David Cowburn
David Cowburn, Michael Rout
Improving the Hole Picture: Towards a Consensus on the Mechanism of Nuclear Transport
null
null
null
null
q-bio.BM
http://creativecommons.org/licenses/by/4.0/
Nuclear pore complexes (NPCs) mediate the exchange of materials between the nucleoplasm and cytoplasm, playing a key role in the separation of nucleic acids and proteins into their required compartments. The static structure of the NPC is relatively well defined by recent cryo EM and other studies. The functional roles of dynamic components in the pore of the NPC, phenylalanyl-glycyl (FG) repeat rich nucleoporins, is less clear because of our limited understanding of highly dynamic protein systems. These proteins form a restrained concentrate which interacts with and concentrates nuclear transport factors (NTRs) to provide facilitated nucleocytoplasmic transport of cargoes. Very rapid exchange among FG repeats and NTRs supports extremely fast facilitated transport, close to the rate of macromolecular diffusion in cytoplasm, while complexes without specific interactions are entropically excluded, though details on several aspects of the transport mechanism and FG repeat behaviors remain to be resolved. However, as discussed here, new technical approaches combined with more advanced modeling methods will likely provide an improved dynamic description of NPC transport, potentially at the atomic level in the near future. Such advances are likely to be of major benefit in comprehending the roles the malfunctioning NPC plays in cancer, aging, viral diseases, and neurodegeneration.
[ { "created": "Thu, 6 Apr 2023 17:04:53 GMT", "version": "v1" } ]
2023-04-07
[ [ "Cowburn", "David", "" ], [ "Rout", "Michael", "" ] ]
Nuclear pore complexes (NPCs) mediate the exchange of materials between the nucleoplasm and cytoplasm, playing a key role in the separation of nucleic acids and proteins into their required compartments. The static structure of the NPC is relatively well defined by recent cryo EM and other studies. The functional roles of dynamic components in the pore of the NPC, phenylalanyl-glycyl (FG) repeat rich nucleoporins, is less clear because of our limited understanding of highly dynamic protein systems. These proteins form a restrained concentrate which interacts with and concentrates nuclear transport factors (NTRs) to provide facilitated nucleocytoplasmic transport of cargoes. Very rapid exchange among FG repeats and NTRs supports extremely fast facilitated transport, close to the rate of macromolecular diffusion in cytoplasm, while complexes without specific interactions are entropically excluded, though details on several aspects of the transport mechanism and FG repeat behaviors remain to be resolved. However, as discussed here, new technical approaches combined with more advanced modeling methods will likely provide an improved dynamic description of NPC transport, potentially at the atomic level in the near future. Such advances are likely to be of major benefit in comprehending the roles the malfunctioning NPC plays in cancer, aging, viral diseases, and neurodegeneration.
1612.03125
Yoav Kallus
Yoav Kallus, John H. Miller, Eric Libby
Paradoxes in Leaky Microbial Trade
source includes supplemental code
Nature Communications 8, 1361 (2017)
10.1038/s41467-017-01628-8
null
q-bio.PE physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Microbes produce metabolic resources that are important for cell growth yet leak across membranes into the extracellular environment. Other microbes in the same environment can use these resources and adjust their own metabolic production accordingly---causing other resources to leak into the environment. The combined effect of these processes is an economy in which organismal growth and metabolic production are coupled to others in the community. We propose a model for the co-evolving dynamics of metabolite concentrations, production regulation, and population frequencies for the case of two cell types, each requiring and capable of producing two metabolites. In this model, beneficial trade relations emerge without any coordination, via individual-level production decisions that maximize each cell's growth rate given its perceived environment. As we vary production parameters of the model, we encounter three paradoxical behaviors, where a change that should intuitively benefit some cell type, actually harms it. (1) If a cell type is more efficient than its counterpart at producing a metabolite and becomes even more efficient, its frequency in the population can decrease. (2) If a cell type is less efficient than its counterpart at producing a metabolite but becomes less inefficient, the growth rate of the population can decrease. (3) Finally, if a cell type controls its counterpart's production decisions so as to maximize its own growth rate, the ultimate growth rate it achieves can be lower than if the two cell types each maximized their own growth. These three paradoxes highlight the complex and counter-intuitive dynamics that emerge in simple microbial economies.
[ { "created": "Fri, 9 Dec 2016 18:48:19 GMT", "version": "v1" } ]
2018-01-16
[ [ "Kallus", "Yoav", "" ], [ "Miller", "John H.", "" ], [ "Libby", "Eric", "" ] ]
Microbes produce metabolic resources that are important for cell growth yet leak across membranes into the extracellular environment. Other microbes in the same environment can use these resources and adjust their own metabolic production accordingly---causing other resources to leak into the environment. The combined effect of these processes is an economy in which organismal growth and metabolic production are coupled to others in the community. We propose a model for the co-evolving dynamics of metabolite concentrations, production regulation, and population frequencies for the case of two cell types, each requiring and capable of producing two metabolites. In this model, beneficial trade relations emerge without any coordination, via individual-level production decisions that maximize each cell's growth rate given its perceived environment. As we vary production parameters of the model, we encounter three paradoxical behaviors, where a change that should intuitively benefit some cell type, actually harms it. (1) If a cell type is more efficient than its counterpart at producing a metabolite and becomes even more efficient, its frequency in the population can decrease. (2) If a cell type is less efficient than its counterpart at producing a metabolite but becomes less inefficient, the growth rate of the population can decrease. (3) Finally, if a cell type controls its counterpart's production decisions so as to maximize its own growth rate, the ultimate growth rate it achieves can be lower than if the two cell types each maximized their own growth. These three paradoxes highlight the complex and counter-intuitive dynamics that emerge in simple microbial economies.
2401.04602
Tual Monfort Dr
Cheryl A. Hawkes, Victoria Goss, Elina Zotova, Tual Monfort, Anthony Postle, Sumeet Mahajan, James A.R. Nicoll, Roy O. Weller and Roxana O. Carare
Impact of maternal high fat on neurovascular unit of adult offspring
45 pages, 7 figures
null
null
null
q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Maternal obesity is associated with increased risk of diabetes, cardiovascular disease and hypertension in adult offspring. Midlife hypercholesterolemia and hypertension are risk factors for Alzheimer's disease, suggesting that the ageing brain may be impacted by early life environment. We found that exposure to a high fat diet during gestation and lactation induced changes in multiple components of the neurovascular unit, including a downregulation in apolipoprotein E and fibronectin, an upregulation in markers of astrocytes and perivascular macrophages and altered blood vessel morphology in the brains of adult mice. Feeding of high fat diet after weaning increased lipid droplets in the brain and influenced the fatty acid composition of phosphatidylcholine and phosphatidylethanolamine species, but did not affect the neurovascular unit. Sustained high fat diet over the entire lifespan resulted in additional decreases in levels of pericytes and collagen IV, changes in phospholipid composition and impaired perivascular clearance of Beta-amyloid (A-Beta) from the brain. In humans, vascular A-Beta load was significantly increased in the brains of aged individuals with a history of hypercholesterolemia. These results support a critical role for early dietary influence on the brain vasculature across the lifespan, with consequences for the development of age-related cerebrovascular and neurodegenerative diseases.
[ { "created": "Tue, 9 Jan 2024 15:17:10 GMT", "version": "v1" } ]
2024-01-10
[ [ "Hawkes", "Cheryl A.", "" ], [ "Goss", "Victoria", "" ], [ "Zotova", "Elina", "" ], [ "Monfort", "Tual", "" ], [ "Postle", "Anthony", "" ], [ "Mahajan", "Sumeet", "" ], [ "Nicoll", "James A. R.", "" ], [ "Weller", "Roy O.", "" ], [ "Carare", "Roxana O.", "" ] ]
Maternal obesity is associated with increased risk of diabetes, cardiovascular disease and hypertension in adult offspring. Midlife hypercholesterolemia and hypertension are risk factors for Alzheimer's disease, suggesting that the ageing brain may be impacted by early life environment. We found that exposure to a high fat diet during gestation and lactation induced changes in multiple components of the neurovascular unit, including a downregulation in apolipoprotein E and fibronectin, an upregulation in markers of astrocytes and perivascular macrophages and altered blood vessel morphology in the brains of adult mice. Feeding of high fat diet after weaning increased lipid droplets in the brain and influenced the fatty acid composition of phosphatidylcholine and phosphatidylethanolamine species, but did not affect the neurovascular unit. Sustained high fat diet over the entire lifespan resulted in additional decreases in levels of pericytes and collagen IV, changes in phospholipid composition and impaired perivascular clearance of Beta-amyloid (A-Beta) from the brain. In humans, vascular A-Beta load was significantly increased in the brains of aged individuals with a history of hypercholesterolemia. These results support a critical role for early dietary influence on the brain vasculature across the lifespan, with consequences for the development of age-related cerebrovascular and neurodegenerative diseases.
1903.02633
J.K. Chen
Jiao-Kai Chen
A novel quantum theory of psychology
11 pages. Part of the manuscript is rewritten and part of it is added
null
null
null
q-bio.NC quant-ph
http://creativecommons.org/licenses/by/4.0/
The behavior coordinate system and the ideal individual model are presented. The behavior state of an ideal individual is assumed to be represented by a behavior state function. Based on the ideal individual model, the behavior coordinate system and the quantum probability, a novel quantum theory of psychology is offered here in a different way. It can give some enlightening viewpoints through which some phenomena can be discussed from a different perspective.
[ { "created": "Tue, 5 Mar 2019 15:49:52 GMT", "version": "v1" }, { "created": "Sun, 2 Jun 2019 03:50:40 GMT", "version": "v2" } ]
2019-06-04
[ [ "Chen", "Jiao-Kai", "" ] ]
The behavior coordinate system and the ideal individual model are presented. The behavior state of an ideal individual is assumed to be represented by a behavior state function. Based on the ideal individual model, the behavior coordinate system and the quantum probability, a novel quantum theory of psychology is offered here in a different way. It can give some enlightening viewpoints through which some phenomena can be discussed from a different perspective.
2202.12236
Kate Duffy
Kate Duffy, Tarik C. Gouhier, and Auroop R. Ganguly
Climate-mediated shifts in temperature fluctuations promote extinction risk
null
Nat. Clim. Chang. 12, 1037-1044 (2022)
10.1038/s41558-022-01490-7
null
q-bio.PE physics.ao-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Climate-mediated changes in the spatiotemporal distribution of thermal stress can destabilize animal populations and promote extinction risk. Using quantile, spectral, and wavelet analyses of temperature projections from the latest generation of earth system models, we show that significant regional differences are expected to arise in the way that temperatures will increase over time. When integrated into empirically-parameterized mathematical models that simulate the dynamical and cumulative effects of thermal stress on the performance of 38 global ectotherm species, the projected spatiotemporal changes in temperature fluctuations are expected to give rise to complex regional changes in population abundance and stability over the course of the 21st century. However, despite their idiosyncratic effects on stability, projected temperatures universally increase extinction risk. These results show that population changes under future climate conditions may be more extensive and complex than the current literature suggests based on the statistical relationship between biological performance and average temperature.
[ { "created": "Wed, 23 Feb 2022 17:45:13 GMT", "version": "v1" }, { "created": "Tue, 20 Dec 2022 21:30:33 GMT", "version": "v2" } ]
2022-12-22
[ [ "Duffy", "Kate", "" ], [ "Gouhier", "Tarik C.", "" ], [ "Ganguly", "Auroop R.", "" ] ]
Climate-mediated changes in the spatiotemporal distribution of thermal stress can destabilize animal populations and promote extinction risk. Using quantile, spectral, and wavelet analyses of temperature projections from the latest generation of earth system models, we show that significant regional differences are expected to arise in the way that temperatures will increase over time. When integrated into empirically-parameterized mathematical models that simulate the dynamical and cumulative effects of thermal stress on the performance of 38 global ectotherm species, the projected spatiotemporal changes in temperature fluctuations are expected to give rise to complex regional changes in population abundance and stability over the course of the 21st century. However, despite their idiosyncratic effects on stability, projected temperatures universally increase extinction risk. These results show that population changes under future climate conditions may be more extensive and complex than the current literature suggests based on the statistical relationship between biological performance and average temperature.
q-bio/0412024
Henrik Jeldtoft Jensen
Daniel Lawson and Henrik Jeldtoft Jensen
The species-area relationship and evolution
21 pages, 5 figures. This is the final, accepted draft
Journal of Theoretical Biology, 2006, vol 241:590-600
10.1016/j.jtbi.2005.12.018
null
q-bio.PE
null
Models relating to the Species-Area curve are usually defined at the species level, and concerned only with ecological timescales. We examine an individual-based model of co-evolution on a spatial lattice based on the Tangled Nature model, and show that reproduction, mutation and dispersion by diffusion in an interacting system produces power-law Species-Area Relations as observed in ecological measurements at medium scales. We find that co-evolutionary habitats form, allowing high diversity levels in a spatially homogenous system, and these are maintained for exponentially increasing time when increasing system size.
[ { "created": "Mon, 13 Dec 2004 15:43:55 GMT", "version": "v1" }, { "created": "Sun, 10 Sep 2006 20:25:25 GMT", "version": "v2" } ]
2007-05-23
[ [ "Lawson", "Daniel", "" ], [ "Jensen", "Henrik Jeldtoft", "" ] ]
Models relating to the Species-Area curve are usually defined at the species level, and concerned only with ecological timescales. We examine an individual-based model of co-evolution on a spatial lattice based on the Tangled Nature model, and show that reproduction, mutation and dispersion by diffusion in an interacting system produces power-law Species-Area Relations as observed in ecological measurements at medium scales. We find that co-evolutionary habitats form, allowing high diversity levels in a spatially homogenous system, and these are maintained for exponentially increasing time when increasing system size.
0908.3923
Vadim N. Biktashev
R. D. Simitev and V. N. Biktashev
Asymptotics of conduction velocity restitution in models of electrical excitation in the heart
39 pages, 12 figures, as accepted to Bull Math Biol 2010/02/12
null
null
null
q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We extend a non-Tikhonov asymptotic embedding, proposed earlier, for calculation of conduction velocity restitution curves in ionic models of cardiac excitability. Conduction velocity restitution is the simplest nontrivial spatially extended problem in excitable media, and in the case of cardiac tissue it is an important tool for prediction of cardiac arrhythmias and fibrillation. An idealized conduction velocity restitution curve requires solving a nonlinear eigenvalue problem with periodic boundary conditions, which in the cardiac case is very stiff and calls for the use of asymptotic methods. We compare asymptotics of restitution curves in four examples, two generic excitable media models, and two ionic cardiac models. The generic models include the classical FitzHugh-Nagumo model and its variation by Barkley. They are treated with standard singular perturbation techniques. The ionic models include a simplified "caricature" of the Noble (1962) model and the Beeler and Reuter (1977) model, which lead to non-Tikhonov problems where known asymptotic results do not apply. The Caricature Noble model is considered with particular care to demonstrate the well-posedness of the corresponding boundary-value problem. The developed method for calculation of conduction velocity restitution is then applied to the Beeler-Reuter model. We discuss new mathematical features appearing in cardiac ionic models and possible applications of the developed method.
[ { "created": "Thu, 27 Aug 2009 13:38:03 GMT", "version": "v1" }, { "created": "Fri, 12 Feb 2010 15:01:22 GMT", "version": "v2" } ]
2010-02-12
[ [ "Simitev", "R. D.", "" ], [ "Biktashev", "V. N.", "" ] ]
We extend a non-Tikhonov asymptotic embedding, proposed earlier, for calculation of conduction velocity restitution curves in ionic models of cardiac excitability. Conduction velocity restitution is the simplest nontrivial spatially extended problem in excitable media, and in the case of cardiac tissue it is an important tool for prediction of cardiac arrhythmias and fibrillation. An idealized conduction velocity restitution curve requires solving a nonlinear eigenvalue problem with periodic boundary conditions, which in the cardiac case is very stiff and calls for the use of asymptotic methods. We compare asymptotics of restitution curves in four examples, two generic excitable media models, and two ionic cardiac models. The generic models include the classical FitzHugh-Nagumo model and its variation by Barkley. They are treated with standard singular perturbation techniques. The ionic models include a simplified "caricature" of the Noble (1962) model and the Beeler and Reuter (1977) model, which lead to non-Tikhonov problems where known asymptotic results do not apply. The Caricature Noble model is considered with particular care to demonstrate the well-posedness of the corresponding boundary-value problem. The developed method for calculation of conduction velocity restitution is then applied to the Beeler-Reuter model. We discuss new mathematical features appearing in cardiac ionic models and possible applications of the developed method.
2406.13765
Jay Lennon
Daniel Henrik Nevermann, Claudius Gros, Jay T. Lennon
A game of life with dormancy
null
null
null
null
q-bio.PE
http://creativecommons.org/licenses/by-sa/4.0/
The factors contributing to the persistence and stability of life are fundamental for understanding complex living systems. Organisms are commonly challenged by harsh and fluctuating environments that are suboptimal for growth and reproduction, which can lead to extinction. Species often contend with unfavorable and noisy conditions by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. Here, we develop Spore Life, a model to investigate the effects of dormancy on population dynamics. It is based on Conway's Game of Life, a deterministic cellular automaton where simple rules govern the metabolic state of an individual based on the metabolic state of its neighbors. For individuals that would otherwise die, Spore Life provides a refuge in the form of an inactive state. These dormant individuals (spores) can resuscitate when local conditions improve. The model includes a parameter alpha that controls the survival probability of spores, interpolating between Game of Life (alpha = 0) and Spore Life (alpha = 1), while capturing stochastic dynamics in the intermediate regime (0 < alpha < 1). In addition to identifying the emergence of unique periodic configurations, we find that spore survival increases the average number of active individuals and buffers populations from extinction. Contrary to expectations, the stabilization of the population is not the result of a large and long-lived seed bank. Instead, the demographic patterns in Spore Life only require a small number of resuscitation events. Our approach yields novel insight into what is minimally required for the emergence of complex behaviors associated with dormancy and the seed banks that they generate.
[ { "created": "Wed, 19 Jun 2024 18:26:19 GMT", "version": "v1" } ]
2024-06-21
[ [ "Nevermann", "Daniel Henrik", "" ], [ "Gros", "Claudius", "" ], [ "Lennon", "Jay T.", "" ] ]
The factors contributing to the persistence and stability of life are fundamental for understanding complex living systems. Organisms are commonly challenged by harsh and fluctuating environments that are suboptimal for growth and reproduction, which can lead to extinction. Species often contend with unfavorable and noisy conditions by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. Here, we develop Spore Life, a model to investigate the effects of dormancy on population dynamics. It is based on Conway's Game of Life, a deterministic cellular automaton where simple rules govern the metabolic state of an individual based on the metabolic state of its neighbors. For individuals that would otherwise die, Spore Life provides a refuge in the form of an inactive state. These dormant individuals (spores) can resuscitate when local conditions improve. The model includes a parameter alpha that controls the survival probability of spores, interpolating between Game of Life (alpha = 0) and Spore Life (alpha = 1), while capturing stochastic dynamics in the intermediate regime (0 < alpha < 1). In addition to identifying the emergence of unique periodic configurations, we find that spore survival increases the average number of active individuals and buffers populations from extinction. Contrary to expectations, the stabilization of the population is not the result of a large and long-lived seed bank. Instead, the demographic patterns in Spore Life only require a small number of resuscitation events. Our approach yields novel insight into what is minimally required for the emergence of complex behaviors associated with dormancy and the seed banks that they generate.
2202.03985
Tyler Meadows
Tyler Meadows, Elissa J. Schwartz
A model of virus infection with immune responses supports boosting CTL response to balance antibody response
null
null
null
null
q-bio.PE
http://creativecommons.org/licenses/by/4.0/
We analyze a within-host model of virus infection with antibody and CD8+ cytotoxic T lymphocyte (CTL) responses proposed by Schwartz et al. (2013). The goal of this work is to gain an overview of the stability of the biologically-relevant equilibria as a function of the model's immune response parameters. We show that the equilibria undergo at most two forward transcritical bifurcations. The model is also explored numerically and results are applied to equine infectious anemia virus infection. In order to arrive at stability of the biologically-relevant endemic equilibrium characterized by coexistence of antibody and CTL responses, the parameters promoting CTL responses need to be boosted over parameters promoting antibody production. This result may seem counter-intuitive (in that a weaker antibody response is better) but can be understood in terms of a balance between CTL and antibody responses that is needed to permit existence of CTLs. In conclusion, an intervention such as a vaccine that is intended to control a persistent viral infection with both immune responses should moderate the antibody response to allow for stimulation of the CTL response.
[ { "created": "Tue, 8 Feb 2022 16:42:41 GMT", "version": "v1" }, { "created": "Fri, 11 Feb 2022 15:01:13 GMT", "version": "v2" } ]
2022-02-14
[ [ "Meadows", "Tyler", "" ], [ "Schwartz", "Elissa J.", "" ] ]
We analyze a within-host model of virus infection with antibody and CD8+ cytotoxic T lymphocyte (CTL) responses proposed by Schwartz et al. (2013). The goal of this work is to gain an overview of the stability of the biologically-relevant equilibria as a function of the model's immune response parameters. We show that the equilibria undergo at most two forward transcritical bifurcations. The model is also explored numerically and results are applied to equine infectious anemia virus infection. In order to arrive at stability of the biologically-relevant endemic equilibrium characterized by coexistence of antibody and CTL responses, the parameters promoting CTL responses need to be boosted over parameters promoting antibody production. This result may seem counter-intuitive (in that a weaker antibody response is better) but can be understood in terms of a balance between CTL and antibody responses that is needed to permit existence of CTLs. In conclusion, an intervention such as a vaccine that is intended to control a persistent viral infection with both immune responses should moderate the antibody response to allow for stimulation of the CTL response.
2105.03903
Benjamin Wingfield Dr
Benjamin Wingfield, Sonya Coleman, T. M. McGinnity, Anthony J. Bjourson
Rough Set Microbiome Characterisation
8 pages, 2 figures
null
null
null
q-bio.QM
http://creativecommons.org/licenses/by-nc-nd/4.0/
Microbiota profiles measure the structure of microbial communities in a defined environment (known as microbiomes). In the past decade, microbiome research has focused on health applications as a result of which the gut microbiome has been implicated in the development of a broad range of diseases such as obesity, inflammatory bowel disease, and major depressive disorder. A key goal of many microbiome experiments is to characterise or describe the microbial community. High-throughput sequencing is used to generate microbiota profiles, but data gathered via this method are extremely challenging to analyse, as the data violate multiple strong assumptions of standard models. Rough Set Theory (RST) has weak assumptions that are less likely to be violated, and offers a range of attractive tools for extracting knowledge from complex data. In this paper we present the first application of RST for characterising microbiomes. We begin with a demonstrative benchmark microbiota profile and extend the approach to gut microbiomes gathered from depressed subjects to enable knowledge discovery. We find that RST is capable of excellent characterisation of the gut microbiomes in depressed subjects and identifying previously undescribed alterations to the microbiome-gut-brain axis. An important aspect of the application of RST is that it provides a possible solution to an open research question regarding the search for an optimal normalisation approach for microbiome census data, as one does not currently exist.
[ { "created": "Sun, 9 May 2021 10:35:05 GMT", "version": "v1" } ]
2021-05-11
[ [ "Wingfield", "Benjamin", "" ], [ "Coleman", "Sonya", "" ], [ "McGinnity", "T. M.", "" ], [ "Bjourson", "Anthony J.", "" ] ]
Microbiota profiles measure the structure of microbial communities in a defined environment (known as microbiomes). In the past decade, microbiome research has focused on health applications as a result of which the gut microbiome has been implicated in the development of a broad range of diseases such as obesity, inflammatory bowel disease, and major depressive disorder. A key goal of many microbiome experiments is to characterise or describe the microbial community. High-throughput sequencing is used to generate microbiota profiles, but data gathered via this method are extremely challenging to analyse, as the data violate multiple strong assumptions of standard models. Rough Set Theory (RST) has weak assumptions that are less likely to be violated, and offers a range of attractive tools for extracting knowledge from complex data. In this paper we present the first application of RST for characterising microbiomes. We begin with a demonstrative benchmark microbiota profile and extend the approach to gut microbiomes gathered from depressed subjects to enable knowledge discovery. We find that RST is capable of excellent characterisation of the gut microbiomes in depressed subjects and identifying previously undescribed alterations to the microbiome-gut-brain axis. An important aspect of the application of RST is that it provides a possible solution to an open research question regarding the search for an optimal normalisation approach for microbiome census data, as one does not currently exist.
1912.05724
Vincent Voelz
Hongbin Wan and Vincent A. Voelz
Adaptive Markov State Model estimation using short reseeding trajectories
null
null
10.1063/1.5142457
null
q-bio.BM cond-mat.stat-mech
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the last decade, advances in molecular dynamics (MD) and Markov State Model (MSM) methodologies have made possible accurate and efficient estimation of kinetic rates and reactive pathways for complex biomolecular dynamics occurring on slow timescales. A promising approach to enhanced sampling of MSMs is to use so-called "adaptive" methods, in which new MD trajectories are "seeded" preferentially from previously identified states. Here, we investigate the performance of various MSM estimators applied to reseeding trajectory data, for both a simple 1D free energy landscape, and for mini-protein folding MSMs of WW domain and NTL9(1-39). Our results reveal the practical challenges of reseeding simulations, and suggest a simple way to reweight seeding trajectory data to better estimate both thermodynamic and kinetic quantities.
[ { "created": "Thu, 12 Dec 2019 01:55:27 GMT", "version": "v1" } ]
2020-01-29
[ [ "Wan", "Hongbin", "" ], [ "Voelz", "Vincent A.", "" ] ]
In the last decade, advances in molecular dynamics (MD) and Markov State Model (MSM) methodologies have made possible accurate and efficient estimation of kinetic rates and reactive pathways for complex biomolecular dynamics occurring on slow timescales. A promising approach to enhanced sampling of MSMs is to use so-called "adaptive" methods, in which new MD trajectories are "seeded" preferentially from previously identified states. Here, we investigate the performance of various MSM estimators applied to reseeding trajectory data, for both a simple 1D free energy landscape, and for mini-protein folding MSMs of WW domain and NTL9(1-39). Our results reveal the practical challenges of reseeding simulations, and suggest a simple way to reweight seeding trajectory data to better estimate both thermodynamic and kinetic quantities.
q-bio/0611023
Per Arne Rikvold
Per Arne Rikvold and Volkan Sevim (Florida State Univ.)
An individual-based predator-prey model for biological coevolution: Fluctuations, stability, and community structure
28 pages, 18 figures. Significantly expanded discussion of community structure and comparison with real food webs. Phys. Rev. E accepted
Phys. REv. E 75, 051920 (2007). (17 pages)
10.1103/PhysRevE.75.051920
null
q-bio.PE cond-mat.stat-mech nlin.AO
null
We study an individual-based predator-prey model of biological coevolution, using linear stability analysis and large-scale kinetic Monte Carlo simulations. The model exhibits approximate 1/f noise in diversity and population-size fluctuations, and it generates a sequence of quasi-steady communities in the form of simple food webs. These communities are quite resilient toward the loss of one or a few species, which is reflected in different power-law exponents for the durations of communities and the lifetimes of species. The exponent for the former is near -1, while the latter is close to -2. Statistical characteristics of the evolving communities, including degree (predator and prey) distributions and proportions of basal, intermediate, and top species, compare reasonably with data for real food webs.
[ { "created": "Tue, 7 Nov 2006 00:16:21 GMT", "version": "v1" }, { "created": "Tue, 24 Apr 2007 22:44:00 GMT", "version": "v2" } ]
2007-06-13
[ [ "Rikvold", "Per Arne", "", "Florida State Univ." ], [ "Sevim", "Volkan", "", "Florida State Univ." ] ]
We study an individual-based predator-prey model of biological coevolution, using linear stability analysis and large-scale kinetic Monte Carlo simulations. The model exhibits approximate 1/f noise in diversity and population-size fluctuations, and it generates a sequence of quasi-steady communities in the form of simple food webs. These communities are quite resilient toward the loss of one or a few species, which is reflected in different power-law exponents for the durations of communities and the lifetimes of species. The exponent for the former is near -1, while the latter is close to -2. Statistical characteristics of the evolving communities, including degree (predator and prey) distributions and proportions of basal, intermediate, and top species, compare reasonably with data for real food webs.
1906.11062
Thomas Heinis
Thomas Heinis, Roman Sokolovskii and Jamie J. Alnasir
Survey of Information Encoding Techniques for DNA
null
null
10.1145/3626233
null
q-bio.QM cs.DB cs.DS cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
The yearly global production of data is growing exponentially, outpacing the capacity of existing storage media, such as tape and disk, and surpassing our ability to store it. DNA storage - the representation of arbitrary information as sequences of nucleotides - offers a promising storage medium. DNA is nature's information-storage molecule of choice and has a number of key properties: it is extremely dense, offering the theoretical possibility of storing 455 EB/g; it is durable, with a half-life of approximately 520 years that can be increased to thousands of years when DNA is chilled and stored dry; and it is amenable to automated synthesis and sequencing. Furthermore, biochemical processes that act on DNA potentially enable highly parallel data manipulation. Whilst biological information is encoded in DNA via a specific mapping from triplet sequences of nucleotides to amino acids, DNA storage is not limited to a single encoding scheme, and there are many possible ways to map data to chemical sequences of nucleotides for synthesis, storage, retrieval and data manipulation. However, there are several biological, error-tolerance and information-retrieval considerations that an encoding scheme needs to address to be viable. This comprehensive review focuses on comparing existing work done in encoding arbitrary data within DNA in terms of their encoding schemes, methods to address biological constraints and measures to provide error correction. We compare encoding approaches on the overall information density and coverage they achieve, as well as the data-retrieval method they use (i.e., sequential or random access). We also discuss the background and evolution of the encoding schemes.
[ { "created": "Mon, 24 Jun 2019 18:57:57 GMT", "version": "v1" }, { "created": "Fri, 27 Aug 2021 15:10:57 GMT", "version": "v2" }, { "created": "Mon, 2 Oct 2023 20:29:58 GMT", "version": "v3" } ]
2023-10-04
[ [ "Heinis", "Thomas", "" ], [ "Sokolovskii", "Roman", "" ], [ "Alnasir", "Jamie J.", "" ] ]
The yearly global production of data is growing exponentially, outpacing the capacity of existing storage media, such as tape and disk, and surpassing our ability to store it. DNA storage - the representation of arbitrary information as sequences of nucleotides - offers a promising storage medium. DNA is nature's information-storage molecule of choice and has a number of key properties: it is extremely dense, offering the theoretical possibility of storing 455 EB/g; it is durable, with a half-life of approximately 520 years that can be increased to thousands of years when DNA is chilled and stored dry; and it is amenable to automated synthesis and sequencing. Furthermore, biochemical processes that act on DNA potentially enable highly parallel data manipulation. Whilst biological information is encoded in DNA via a specific mapping from triplet sequences of nucleotides to amino acids, DNA storage is not limited to a single encoding scheme, and there are many possible ways to map data to chemical sequences of nucleotides for synthesis, storage, retrieval and data manipulation. However, there are several biological, error-tolerance and information-retrieval considerations that an encoding scheme needs to address to be viable. This comprehensive review focuses on comparing existing work done in encoding arbitrary data within DNA in terms of their encoding schemes, methods to address biological constraints and measures to provide error correction. We compare encoding approaches on the overall information density and coverage they achieve, as well as the data-retrieval method they use (i.e., sequential or random access). We also discuss the background and evolution of the encoding schemes.
2402.05750
Luis Fonseca
Luis L. Fonseca, Lucas B\"ottcher, Borna Mehrad, Reinhard C. Laubenbacher
Surrogate Modeling and Control of Medical Digital Twins
50 pages, 4 figures, 22 supplementary figures
null
null
null
q-bio.QM cs.SY eess.SY math.DS math.OC
http://creativecommons.org/licenses/by-sa/4.0/
The vision of personalized medicine is to identify interventions that maintain or restore a person's health based on their individual biology. Medical digital twins, computational models that integrate a wide range of health-related data about a person and can be dynamically updated, are a key technology that can help guide medical decisions. Such medical digital twin models can be high-dimensional, multi-scale, and stochastic. To be practical for healthcare applications, they often need to be simplified into low-dimensional surrogate models that can be used for the optimal design of interventions. This paper introduces surrogate modeling algorithms for the purpose of optimal control applications. As a use case, we focus on agent-based models (ABMs), a common model type in biomedicine for which there are no readily available optimal control algorithms. By deriving surrogate models that are based on systems of ordinary differential equations, we show how optimal control methods can be employed to compute effective interventions, which can then be lifted back to a given ABM. The relevance of the methods introduced here extends beyond medical digital twins to other complex dynamical systems.
[ { "created": "Thu, 8 Feb 2024 15:33:41 GMT", "version": "v1" }, { "created": "Mon, 20 May 2024 13:09:56 GMT", "version": "v2" } ]
2024-05-21
[ [ "Fonseca", "Luis L.", "" ], [ "Böttcher", "Lucas", "" ], [ "Mehrad", "Borna", "" ], [ "Laubenbacher", "Reinhard C.", "" ] ]
The vision of personalized medicine is to identify interventions that maintain or restore a person's health based on their individual biology. Medical digital twins, computational models that integrate a wide range of health-related data about a person and can be dynamically updated, are a key technology that can help guide medical decisions. Such medical digital twin models can be high-dimensional, multi-scale, and stochastic. To be practical for healthcare applications, they often need to be simplified into low-dimensional surrogate models that can be used for the optimal design of interventions. This paper introduces surrogate modeling algorithms for the purpose of optimal control applications. As a use case, we focus on agent-based models (ABMs), a common model type in biomedicine for which there are no readily available optimal control algorithms. By deriving surrogate models that are based on systems of ordinary differential equations, we show how optimal control methods can be employed to compute effective interventions, which can then be lifted back to a given ABM. The relevance of the methods introduced here extends beyond medical digital twins to other complex dynamical systems.
2006.07933
Rekia Cherif
Rekia Cherif
Comparative study of the biological activities of the aqueous extracts of two spontaneous plants harvested in the Algerian Sahara
151 pages, in French, doctoral thesis, Univ of Ghardaia (2020)
null
null
null
q-bio.OT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The present study investigates the insecticidal and herbicidal effects of leaf extracts from two plants were harvested in the Northern Algerian Sahara. These are Cleome arabica (Capparaceae) and Pergularia tomentosa (Asclepiadaceae). The efficacy of the extracts from the plants was evaluated by the reflux extraction method. The phytochemical screening of the aqueous extracts of C. arabica shows a remarkable richness in active principles in comparison with the extract of P. tomentosa; including flavonoids, saponosides, glycosides, terpenes, sterols, deoxyose, polyphenols and total alkaloids. The imago of Tribolium confusum treated with aqueous extracts of C. arabica and P. tomentosa at doses of 80% to 100% respectively have mortality rates of 73.33% to 96.67%, and 36.67% to 86.67%. The lethal time 50 (TL50%) of the aqueous extract of C. arabica was estimated about 6.41 days, and 6.94 days for the extract P. tomentosa for the imago of T. confusum. The extracts of P. tomentosa is less toxic than the extracts of C. arabica. The allelopathic potentials of C. arabica and P. tomentosa tested on germination of the seeds of a weed Dactyloctenium aegyptium (Poaceae) and two cultivated species, including Hordeumvulgare and Triticumdurum (Poaceae), show that the inhibitory effect of extracts of C. arabica is very highly significant. It manifests itself in the growth of the aerial and underground part of the H. vulgar and T. durum. The inhibition rate is more than 84.44% for D. aegyptium seeds treated with the different concentrations. The inhibition rates range from 75.56% to 91.11% for T. durum wheat irrigate at 80% to 100%, but are only 55.56% to 77.78% for barley seeds treated with the same concentrations (80% to 100%).
[ { "created": "Sun, 14 Jun 2020 15:41:44 GMT", "version": "v1" } ]
2020-06-16
[ [ "Cherif", "Rekia", "" ] ]
The present study investigates the insecticidal and herbicidal effects of leaf extracts from two plants were harvested in the Northern Algerian Sahara. These are Cleome arabica (Capparaceae) and Pergularia tomentosa (Asclepiadaceae). The efficacy of the extracts from the plants was evaluated by the reflux extraction method. The phytochemical screening of the aqueous extracts of C. arabica shows a remarkable richness in active principles in comparison with the extract of P. tomentosa; including flavonoids, saponosides, glycosides, terpenes, sterols, deoxyose, polyphenols and total alkaloids. The imago of Tribolium confusum treated with aqueous extracts of C. arabica and P. tomentosa at doses of 80% to 100% respectively have mortality rates of 73.33% to 96.67%, and 36.67% to 86.67%. The lethal time 50 (TL50%) of the aqueous extract of C. arabica was estimated about 6.41 days, and 6.94 days for the extract P. tomentosa for the imago of T. confusum. The extracts of P. tomentosa is less toxic than the extracts of C. arabica. The allelopathic potentials of C. arabica and P. tomentosa tested on germination of the seeds of a weed Dactyloctenium aegyptium (Poaceae) and two cultivated species, including Hordeumvulgare and Triticumdurum (Poaceae), show that the inhibitory effect of extracts of C. arabica is very highly significant. It manifests itself in the growth of the aerial and underground part of the H. vulgar and T. durum. The inhibition rate is more than 84.44% for D. aegyptium seeds treated with the different concentrations. The inhibition rates range from 75.56% to 91.11% for T. durum wheat irrigate at 80% to 100%, but are only 55.56% to 77.78% for barley seeds treated with the same concentrations (80% to 100%).
1408.0755
Irina Kareva
Irina Kareva
Immune Evasion through Competitive Inhibition: the Shielding Effect of non-Stem Cancer Cells
null
null
null
null
q-bio.TO q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It has been recently proposed that the two "emerging" hallmarks of cancer, namely altered glucose metabolism and immune evasion, may in fact be fundamentally linked (Kareva and Hahnfeldt, 2013). This connection comes from up-regulation of glycolysis by tumor cells, which can lead to active competition for resources in the tumor microenvironment between tumor and immune cells. Here it is further proposed that cancer stem cells (CSCs) can circumvent the anti-tumor immune response by creating a 'protective shield' of non-stem cancer cells around them. This shield can protect the CSCs both by creating a physical barrier between them and cytotoxic lymphocytes (CTLs), and by promoting competition for the common resources, such as glucose, between non-stem cancer cells and CTLs. The implications of this hypothesis are investigate using an agent-based model, leading to a prediction that relative CSC to non-CSC ratio will vary with the strength of the host immune response, with the highest occurring at an intermediate state of immune activation. A discussion of possible therapeutic approaches concludes the paper, suggesting that a chemotherapeutic regimen consisting of regular pulsed doses, i.e., metronomic chemotherapy, would yield the best clinical outcome by allowing CTLs to most effectively reach and eliminate CSCs.
[ { "created": "Mon, 4 Aug 2014 18:06:43 GMT", "version": "v1" } ]
2014-08-05
[ [ "Kareva", "Irina", "" ] ]
It has been recently proposed that the two "emerging" hallmarks of cancer, namely altered glucose metabolism and immune evasion, may in fact be fundamentally linked (Kareva and Hahnfeldt, 2013). This connection comes from up-regulation of glycolysis by tumor cells, which can lead to active competition for resources in the tumor microenvironment between tumor and immune cells. Here it is further proposed that cancer stem cells (CSCs) can circumvent the anti-tumor immune response by creating a 'protective shield' of non-stem cancer cells around them. This shield can protect the CSCs both by creating a physical barrier between them and cytotoxic lymphocytes (CTLs), and by promoting competition for the common resources, such as glucose, between non-stem cancer cells and CTLs. The implications of this hypothesis are investigate using an agent-based model, leading to a prediction that relative CSC to non-CSC ratio will vary with the strength of the host immune response, with the highest occurring at an intermediate state of immune activation. A discussion of possible therapeutic approaches concludes the paper, suggesting that a chemotherapeutic regimen consisting of regular pulsed doses, i.e., metronomic chemotherapy, would yield the best clinical outcome by allowing CTLs to most effectively reach and eliminate CSCs.
1811.12750
Michael Kalyuzhny
Michael Kalyuzhny, Tom Haran and Dror Hawlena
The observation resolution -- a neglected aspect with critical influence on movement-based foraging indices
null
null
null
null
q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Movement-based indices such as moves per minute (MPM) and proportion time moving (PTM) are common methodologies to quantify foraging behaviour. Hundreds of studies have reported these indices without specifying the temporal resolution of their original data, despite the likelihood that the minimal stop and move durations can affect MPM and PTM estimates. Our goal was to empirically determine the sensitivity of these foraging indices to changes in the temporal resolution of the observation. We used a high speed camera to record movement sequences of 20 Acanthodactylus boskianus lizards. We gradually decreased the data resolution by ignoring short stops and either ignoring, elongating or leaving short moves unchanged. We then used the manipulated data to calculate the foraging indices at different temporal resolutions. We found that movement-based indices are very sensitive to the observation resolution, so that realistic variation in the minimal duration of stops and moves could lead to 68 percent and 48 percent difference in MPM and PTM estimates, respectively. When using the highest resolution, our estimate of MPM was an order of magnitude higher than all prior reported values for lizards. Also, the distribution of stop durations was well described by a single heavy tailed distribution above 0.35 seconds. This suggests that for A. boskianus there is no reason to ignore short stops above this threshold. Our results raise major concerns regarding the use of already published movement based indices, and enable us to recommend how new foraging data should be collected.
[ { "created": "Fri, 30 Nov 2018 12:00:00 GMT", "version": "v1" } ]
2018-12-03
[ [ "Kalyuzhny", "Michael", "" ], [ "Haran", "Tom", "" ], [ "Hawlena", "Dror", "" ] ]
Movement-based indices such as moves per minute (MPM) and proportion time moving (PTM) are common methodologies to quantify foraging behaviour. Hundreds of studies have reported these indices without specifying the temporal resolution of their original data, despite the likelihood that the minimal stop and move durations can affect MPM and PTM estimates. Our goal was to empirically determine the sensitivity of these foraging indices to changes in the temporal resolution of the observation. We used a high speed camera to record movement sequences of 20 Acanthodactylus boskianus lizards. We gradually decreased the data resolution by ignoring short stops and either ignoring, elongating or leaving short moves unchanged. We then used the manipulated data to calculate the foraging indices at different temporal resolutions. We found that movement-based indices are very sensitive to the observation resolution, so that realistic variation in the minimal duration of stops and moves could lead to 68 percent and 48 percent difference in MPM and PTM estimates, respectively. When using the highest resolution, our estimate of MPM was an order of magnitude higher than all prior reported values for lizards. Also, the distribution of stop durations was well described by a single heavy tailed distribution above 0.35 seconds. This suggests that for A. boskianus there is no reason to ignore short stops above this threshold. Our results raise major concerns regarding the use of already published movement based indices, and enable us to recommend how new foraging data should be collected.
2003.06092
Samuel Fischer
Samuel M. Fischer, Martina Beck, Leif-Matthias Herborg, Mark A. Lewis
Managing aquatic invasions: optimal locations and operating times for watercraft inspection stations
Keywords: aquatic invasive species; linear integer programming; optimal management; spatially explicit; zebra mussel
Journal of Environmental Management 283 (2021): 111923
10.1016/j.jenvman.2020.111923
null
q-bio.QM math.OC q-bio.PE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Aquatic invasive species (AIS) cause significant ecological and economic damages around the world. A major spread mechanism for AIS is traffic of boaters transporting their watercraft from invaded to uninvaded waterbodies. To inhibit the spread of AIS, several Canadian provinces and American states set up watercraft inspection stations at roadsides, where potentially infested boats are screened for AIS and, if necessary, decontaminated. However, since budgets for AIS control are limited, watercraft inspection stations can only be operated at specific locations and daytimes. Though theoretical studies provide managers with general guidelines for AIS management, more specific results are needed to determine when and where watercraft inspections would be most effective. This is the subject of this paper. We show how linear integer programming techniques can be used to optimize watercraft inspection policies under budget constraints. We introduce our approach as a general framework and apply it to the prevention of the spread of zebra and quagga mussels (Dreissena spp.) to the Canadian province British Columbia. We consider a variety of scenarios and show how variations in budget constraints, propagule sources, and model uncertainty affect the optimal policy. Based on these results, we identify simple, generally applicable principles for optimal AIS management.
[ { "created": "Fri, 13 Mar 2020 03:16:26 GMT", "version": "v1" } ]
2021-05-10
[ [ "Fischer", "Samuel M.", "" ], [ "Beck", "Martina", "" ], [ "Herborg", "Leif-Matthias", "" ], [ "Lewis", "Mark A.", "" ] ]
Aquatic invasive species (AIS) cause significant ecological and economic damages around the world. A major spread mechanism for AIS is traffic of boaters transporting their watercraft from invaded to uninvaded waterbodies. To inhibit the spread of AIS, several Canadian provinces and American states set up watercraft inspection stations at roadsides, where potentially infested boats are screened for AIS and, if necessary, decontaminated. However, since budgets for AIS control are limited, watercraft inspection stations can only be operated at specific locations and daytimes. Though theoretical studies provide managers with general guidelines for AIS management, more specific results are needed to determine when and where watercraft inspections would be most effective. This is the subject of this paper. We show how linear integer programming techniques can be used to optimize watercraft inspection policies under budget constraints. We introduce our approach as a general framework and apply it to the prevention of the spread of zebra and quagga mussels (Dreissena spp.) to the Canadian province British Columbia. We consider a variety of scenarios and show how variations in budget constraints, propagule sources, and model uncertainty affect the optimal policy. Based on these results, we identify simple, generally applicable principles for optimal AIS management.
2012.12127
Dagmar Iber
Dagmar Iber
The Control of Lung Branching Morphogenesis
null
null
null
null
q-bio.TO q-bio.CB q-bio.MN
http://creativecommons.org/licenses/by/4.0/
Branching morphogenesis generates epithelial trees which facilitate gas exchange, filtering, as well as secretion processes with their large surface to volume ratio. In this review, we focus on the developmental mechanisms that control the early stages of lung branching morphogenesis. Lung branching morphogenesis involves the stereotypic, recurrent definition of new branch points, subsequent epithelial budding, and lung tube elongation. We discuss current models and experimental evidence for each of these steps. Finally, we discuss the role of the mesenchyme in determining the organ-specific shape.
[ { "created": "Tue, 22 Dec 2020 16:06:14 GMT", "version": "v1" } ]
2020-12-23
[ [ "Iber", "Dagmar", "" ] ]
Branching morphogenesis generates epithelial trees which facilitate gas exchange, filtering, as well as secretion processes with their large surface to volume ratio. In this review, we focus on the developmental mechanisms that control the early stages of lung branching morphogenesis. Lung branching morphogenesis involves the stereotypic, recurrent definition of new branch points, subsequent epithelial budding, and lung tube elongation. We discuss current models and experimental evidence for each of these steps. Finally, we discuss the role of the mesenchyme in determining the organ-specific shape.
2309.08064
Jinzhi Lei
Jinzhi Lei
Mathematical modeling of heterogeneous stem cell regeneration: from cell division to Waddington's epigenetic landscape
46pages, 1 figures
null
null
null
q-bio.QM
http://creativecommons.org/licenses/by-nc-sa/4.0/
Stem cell regeneration is a crucial biological process for most self-renewing tissues during the development and maintenance of tissue homeostasis. In developing the mathematical models of stem cell regeneration and tissue development, cell division is the core process connecting different scale biological processes and leading to changes in cell population number and the epigenetic state of cells. This chapter focuses on the primary strategies for modeling cell division in biological systems. The Lagrange coordinate modeling approach considers gene network dynamics within each cell and random changes in cell states and model parameters during cell division. In contrast, the Euler coordinate modeling approach formulates the evolution of cell population numbers with the same epigenetic state via a differential-integral equation. These strategies focus on different scale dynamics, respectively, and result in two methods of modeling Waddington's epigenetic landscape: the Fokker-Planck equation and the differential-integral equation approaches. The differential-integral equation approach formulates the evolution of cell population density based on simple assumptions in cell proliferation, apoptosis, differentiation, and epigenetic state transitions during cell division. Moreover, machine learning methods can establish low-dimensional macroscopic measurements of a cell based on single-cell RNA sequencing data. The low dimensional measurements can quantify the epigenetic state of cells and become connections between static single-cell RNA sequencing data with dynamic equations for tissue development processes. The differential-integral equation presented in this chapter provides a reasonable approach to understanding the complex biological processes of tissue development and tumor progression.
[ { "created": "Thu, 14 Sep 2023 23:27:34 GMT", "version": "v1" }, { "created": "Tue, 26 Sep 2023 08:13:21 GMT", "version": "v2" }, { "created": "Tue, 16 Jan 2024 14:39:26 GMT", "version": "v3" } ]
2024-01-17
[ [ "Lei", "Jinzhi", "" ] ]
Stem cell regeneration is a crucial biological process for most self-renewing tissues during the development and maintenance of tissue homeostasis. In developing the mathematical models of stem cell regeneration and tissue development, cell division is the core process connecting different scale biological processes and leading to changes in cell population number and the epigenetic state of cells. This chapter focuses on the primary strategies for modeling cell division in biological systems. The Lagrange coordinate modeling approach considers gene network dynamics within each cell and random changes in cell states and model parameters during cell division. In contrast, the Euler coordinate modeling approach formulates the evolution of cell population numbers with the same epigenetic state via a differential-integral equation. These strategies focus on different scale dynamics, respectively, and result in two methods of modeling Waddington's epigenetic landscape: the Fokker-Planck equation and the differential-integral equation approaches. The differential-integral equation approach formulates the evolution of cell population density based on simple assumptions in cell proliferation, apoptosis, differentiation, and epigenetic state transitions during cell division. Moreover, machine learning methods can establish low-dimensional macroscopic measurements of a cell based on single-cell RNA sequencing data. The low dimensional measurements can quantify the epigenetic state of cells and become connections between static single-cell RNA sequencing data with dynamic equations for tissue development processes. The differential-integral equation presented in this chapter provides a reasonable approach to understanding the complex biological processes of tissue development and tumor progression.
1711.10009
David Guillermo Fajardo Ortiz
David Fajardo-Ortiz, Miguel Lara, and Victor M. Castano
The evolution and structure of biomedical knowledge on cytochrome P450
Three figures and one table
null
null
null
q-bio.OT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cytochrome P450 are fundamental proteins to the metabolism of drugs and other relevant processes. through a combination of text mining and network analysis of the P450 literature we mapped the emergence and evolution of the biomedical research communities working on this family of proteins. Our results suggest that the historical research communities that worked on P450 emerged and were organized mainly around methodological achievements like the induction of animal liver microsomal P450 by drugs, the use of chemical inhibitors of P450 enzymes in in-vitro metabolism studies and the development of E. coli expression systems. We found clear evidence that P450 research indeed constitutes a material scientific culture, as we discuss in the text.
[ { "created": "Mon, 27 Nov 2017 21:37:32 GMT", "version": "v1" } ]
2017-11-29
[ [ "Fajardo-Ortiz", "David", "" ], [ "Lara", "Miguel", "" ], [ "Castano", "Victor M.", "" ] ]
Cytochrome P450 are fundamental proteins to the metabolism of drugs and other relevant processes. through a combination of text mining and network analysis of the P450 literature we mapped the emergence and evolution of the biomedical research communities working on this family of proteins. Our results suggest that the historical research communities that worked on P450 emerged and were organized mainly around methodological achievements like the induction of animal liver microsomal P450 by drugs, the use of chemical inhibitors of P450 enzymes in in-vitro metabolism studies and the development of E. coli expression systems. We found clear evidence that P450 research indeed constitutes a material scientific culture, as we discuss in the text.
1208.4613
Laure Segurel
Laure S\'egurel, Emma E. Thompson, Timoth\'ee Flutre, Jessica Lovstad, Aarti Venkat, Susan W. Margulis, Jill Moyse, Steve Ross, Kathryn Gamble, Guy Sella, Carole Ober, Molly Przeworski
Blood ties: ABO is a trans-species polymorphism in primates
45 pages, 4 Figures, 4 Supplementary Figures, 5 Supplementary Tables
null
10.1073/pnas.1210603109
null
q-bio.PE q-bio.GN
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ABO histo-blood group, the critical determinant of transfusion incompatibility, was the first genetic polymorphism discovered in humans. Remarkably, ABO antigens are also polymorphic in many other primates, with the same two amino acid changes responsible for A and B specificity in all species sequenced to date. Whether this recurrence of A and B antigens is the result of an ancient polymorphism maintained across species or due to numerous, more recent instances of convergent evolution has been debated for decades, with a current consensus in support of convergent evolution. We show instead that genetic variation data in humans and gibbons as well as in Old World Monkeys are inconsistent with a model of convergent evolution and support the hypothesis of an ancient, multi-allelic polymorphism of which some alleles are shared by descent among species. These results demonstrate that the ABO polymorphism is a trans-species polymorphism among distantly related species and has remained under balancing selection for tens of millions of years, to date, the only such example in Hominoids and Old World Monkeys outside of the Major Histocompatibility Complex.
[ { "created": "Wed, 22 Aug 2012 20:21:37 GMT", "version": "v1" } ]
2015-06-11
[ [ "Ségurel", "Laure", "" ], [ "Thompson", "Emma E.", "" ], [ "Flutre", "Timothée", "" ], [ "Lovstad", "Jessica", "" ], [ "Venkat", "Aarti", "" ], [ "Margulis", "Susan W.", "" ], [ "Moyse", "Jill", "" ], [ "Ross", "Steve", "" ], [ "Gamble", "Kathryn", "" ], [ "Sella", "Guy", "" ], [ "Ober", "Carole", "" ], [ "Przeworski", "Molly", "" ] ]
The ABO histo-blood group, the critical determinant of transfusion incompatibility, was the first genetic polymorphism discovered in humans. Remarkably, ABO antigens are also polymorphic in many other primates, with the same two amino acid changes responsible for A and B specificity in all species sequenced to date. Whether this recurrence of A and B antigens is the result of an ancient polymorphism maintained across species or due to numerous, more recent instances of convergent evolution has been debated for decades, with a current consensus in support of convergent evolution. We show instead that genetic variation data in humans and gibbons as well as in Old World Monkeys are inconsistent with a model of convergent evolution and support the hypothesis of an ancient, multi-allelic polymorphism of which some alleles are shared by descent among species. These results demonstrate that the ABO polymorphism is a trans-species polymorphism among distantly related species and has remained under balancing selection for tens of millions of years, to date, the only such example in Hominoids and Old World Monkeys outside of the Major Histocompatibility Complex.
0908.3600
Thimo Rohlf
Thimo Rohlf and Stefan Bornholdt
Morphogenesis by coupled regulatory networks: Reliable control of positional information and proportion regulation
Journal of Theoretical Biology, in press
null
10.1016/j.jtbi.2009.07.023
null
q-bio.MN cond-mat.dis-nn nlin.CG q-bio.CB q-bio.TO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Based on a non-equilibrium mechanism for spatial pattern formation we study how position information can be controlled by locally coupled discrete dynamical networks, similar to gene regulation networks of cells in a developing multicellular organism. As an example we study the developmental problems of domain formation and proportion regulation in the presence of noise, as well as in the presence of cell flow. We find that networks that solve this task exhibit a hierarchical structure of information processing and are of similar complexity as developmental circuits of living cells. Proportion regulation is scalable with system size and leads to sharp, precisely localized boundaries of gene expression domains, even for large numbers of cells. A detailed analysis of noise-induced dynamics, using a mean-field approximation, shows that noise in gene expression states stabilizes (rather than disrupts) the spatial pattern in the presence of cell movements, both for stationary as well as growing systems. Finally, we discuss how this mechanism could be realized in the highly dynamic environment of growing tissues in multi-cellular organisms.
[ { "created": "Tue, 25 Aug 2009 12:18:29 GMT", "version": "v1" } ]
2009-08-26
[ [ "Rohlf", "Thimo", "" ], [ "Bornholdt", "Stefan", "" ] ]
Based on a non-equilibrium mechanism for spatial pattern formation we study how position information can be controlled by locally coupled discrete dynamical networks, similar to gene regulation networks of cells in a developing multicellular organism. As an example we study the developmental problems of domain formation and proportion regulation in the presence of noise, as well as in the presence of cell flow. We find that networks that solve this task exhibit a hierarchical structure of information processing and are of similar complexity as developmental circuits of living cells. Proportion regulation is scalable with system size and leads to sharp, precisely localized boundaries of gene expression domains, even for large numbers of cells. A detailed analysis of noise-induced dynamics, using a mean-field approximation, shows that noise in gene expression states stabilizes (rather than disrupts) the spatial pattern in the presence of cell movements, both for stationary as well as growing systems. Finally, we discuss how this mechanism could be realized in the highly dynamic environment of growing tissues in multi-cellular organisms.
2210.10905
Ian Knight
Ian Scott Knight, Slava Naprienko, John J. Irwin
Enrichment Score: a better quantitative metric for evaluating the enrichment capacity of molecular docking models
null
null
null
null
q-bio.QM stat.AP
http://creativecommons.org/licenses/by-sa/4.0/
The standard quantitative metric for evaluating enrichment capacity known as $\textit{LogAUC}$ depends on a cutoff parameter that controls what the minimum value of the log-scaled x-axis is. Unless this parameter is chosen carefully for a given ROC curve, one of the two following problems occurs: either (1) some fraction of the first inter-decoy intervals of the ROC curve are simply thrown away and do not contribute to the metric at all, or (2) the very first inter-decoy interval contributes too much to the metric at the expense of all following inter-decoy intervals. We fix this problem with LogAUC by showing a simple way to choose the cutoff parameter based on the number of decoys which forces the first inter-decoy interval to always have a stable, sensible contribution to the total value. Moreover, we introduce a normalized version of LogAUC known as $\textit{enrichment score}$, which (1) enforces stability by selecting the cutoff parameter in the manner described, (2) yields scores which are more intuitively meaningful, and (3) allows reliably accurate comparison of the enrichment capacities exhibited by different ROC curves, even those produced using different numbers of decoys. Finally, we demonstrate the advantage of enrichment score over unbalanced metrics using data from a real retrospective docking study performed using the program $\textit{DOCK 3.7}$ on the target receptor TRYB1 included in the $\textit{DUDE-Z}$ benchmark.
[ { "created": "Wed, 19 Oct 2022 22:02:55 GMT", "version": "v1" }, { "created": "Mon, 21 Nov 2022 22:57:36 GMT", "version": "v2" }, { "created": "Thu, 24 Nov 2022 22:04:44 GMT", "version": "v3" }, { "created": "Mon, 22 May 2023 01:44:48 GMT", "version": "v4" } ]
2023-05-23
[ [ "Knight", "Ian Scott", "" ], [ "Naprienko", "Slava", "" ], [ "Irwin", "John J.", "" ] ]
The standard quantitative metric for evaluating enrichment capacity known as $\textit{LogAUC}$ depends on a cutoff parameter that controls what the minimum value of the log-scaled x-axis is. Unless this parameter is chosen carefully for a given ROC curve, one of the two following problems occurs: either (1) some fraction of the first inter-decoy intervals of the ROC curve are simply thrown away and do not contribute to the metric at all, or (2) the very first inter-decoy interval contributes too much to the metric at the expense of all following inter-decoy intervals. We fix this problem with LogAUC by showing a simple way to choose the cutoff parameter based on the number of decoys which forces the first inter-decoy interval to always have a stable, sensible contribution to the total value. Moreover, we introduce a normalized version of LogAUC known as $\textit{enrichment score}$, which (1) enforces stability by selecting the cutoff parameter in the manner described, (2) yields scores which are more intuitively meaningful, and (3) allows reliably accurate comparison of the enrichment capacities exhibited by different ROC curves, even those produced using different numbers of decoys. Finally, we demonstrate the advantage of enrichment score over unbalanced metrics using data from a real retrospective docking study performed using the program $\textit{DOCK 3.7}$ on the target receptor TRYB1 included in the $\textit{DUDE-Z}$ benchmark.
2408.02640
Suman Kulkarni
Suman Kulkarni and Dani S. Bassett
Towards principles of brain network organization and function
Submitted to Annual Review of Biophysics. Comments welcome. When citing this paper, please use the following: Kulkarni S, Bassett DS. 2025. Towards Principles of Brain Network Organization and Function. Annu. Rev. Biophys. 54: Submitted. DOI: 10.1146/annurev-biophys-030722-110624
null
null
null
q-bio.NC cond-mat.stat-mech physics.bio-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The brain is immensely complex, with diverse components and dynamic interactions building upon one another to orchestrate a wide range of functions and behaviors. Understanding patterns of these complex interactions and how they are coordinated to support collective neural activity and function is critical for parsing human and animal behavior, treating mental illness, and developing artificial intelligence. Rapid experimental advances in imaging, recording, and perturbing neural systems across various species now provide opportunities and challenges to distill underlying principles of brain organization and function. Here, we take stock of recent progresses and review methods used in the statistical analysis of brain networks, drawing from fields of statistical physics, network theory and information theory. Our discussion is organized by scale, starting with models of individual neurons and extending to large-scale networks mapped across brain regions. We then examine the organizing principles and constraints that shape the biological structure and function of neural circuits. Finally, we describe current opportunities aimed at improving models in light of recent developments and at bridging across scales to contribute to a better understanding of brain networks.
[ { "created": "Mon, 5 Aug 2024 17:13:10 GMT", "version": "v1" } ]
2024-08-06
[ [ "Kulkarni", "Suman", "" ], [ "Bassett", "Dani S.", "" ] ]
The brain is immensely complex, with diverse components and dynamic interactions building upon one another to orchestrate a wide range of functions and behaviors. Understanding patterns of these complex interactions and how they are coordinated to support collective neural activity and function is critical for parsing human and animal behavior, treating mental illness, and developing artificial intelligence. Rapid experimental advances in imaging, recording, and perturbing neural systems across various species now provide opportunities and challenges to distill underlying principles of brain organization and function. Here, we take stock of recent progresses and review methods used in the statistical analysis of brain networks, drawing from fields of statistical physics, network theory and information theory. Our discussion is organized by scale, starting with models of individual neurons and extending to large-scale networks mapped across brain regions. We then examine the organizing principles and constraints that shape the biological structure and function of neural circuits. Finally, we describe current opportunities aimed at improving models in light of recent developments and at bridging across scales to contribute to a better understanding of brain networks.