PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Theoretical biology"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&unformattedQuery=subject:%22Theoretical+biology%22&sort=Date,+newest+firstAll PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-29T06:27:38ZShibboleth: An agent-based model of signalling mimicryJonathan R. GoodmanAndrew CainesRobert A. Foley10.1371/journal.pone.02893332023-07-31T14:00:00Z2023-07-31T14:00:00Z<p>by Jonathan R. Goodman, Andrew Caines, Robert A. Foley</p>
Mimicry is an essential strategy for exploiting competitors in competitive co-evolutionary relationships. Protection against mimicry may, furthermore, be a driving force in human linguistic diversity: the potential harm caused by failing to detect mimicked group-identity signals may select for high sensitivity to mimicry of honest group members. Here we describe the results of five agent-based models that simulate multi-generational interactions between two groups of individuals: original members of a group with an honest identity signal, and members of an outsider group who mimic that signal, aiming to pass as members of the in-group. The models correspond to the Biblical story of Shibboleth, where a tribe in conflict with another determines tribe affiliation by asking individuals to pronounce the word, ‘Shibboleth.’ In the story, failure to reproduce the word phonetically resulted in death. Here, we run five different versions of a ‘Shibboleth’ model: a first, simple version, which evaluates whether a composite variable of mimicry quality and detection quality is a superior predictor to the model’s outcome than is cost of detection. The models thereafter evaluate variations on the simple model, incorporating group-level behaviours such as altruistic punishment. Our results suggest that group members’ sensitivity to mimicry of the Shibboleth-signal is a better predictor of whether any signal of group identity goes into fixation in the overall population than is the cost of mimicry detection. Thus, the likelihood of being detected as a mimic may be more important than the costs imposed on mimics who are detected. This suggests that theoretical models in biology should place greater emphasis on the likelihood of detection, which does not explicitly entail costs, rather than on the costs to individuals who are detected. From a language learning perspective, the results suggest that admission to group membership through linguistic signals is powered by the ability to imitate and evade detection as an outsider by existing group members.Exact solutions of (1 + 1)-dimensional integro-differential Ito, KP hierarchy, CBS, MCBS and modified KdV-CBS equationsAmina AminImran NaeemAdnan Khan10.1371/journal.pone.02835692023-03-30T14:00:00Z2023-03-30T14:00:00Z<p>by Amina Amin, Imran Naeem, Adnan Khan</p>
The present study computes the Lie symmetries and exact solutions of some problems modeled by nonlinear partial differential equations. The (1 + 1)-dimensional integro-differential Ito, the first integro-differential KP hierarchy, the Calogero-Bogoyavlenskii-Schiff (CBS), the modified Calogero-Bogoyavlenskii-Schiff (CBS), and the modified KdV-CBS equations are some of the problems for which we want to find new exact solutions. We employ similarity variables to reduce the number of independent variables and inverse similarity transformations to obtain exact solutions to the equations under consideration. The sine-cosine method is then utilized to determine the exact solutions.The global convergence of spectral RMIL conjugate gradient method for unconstrained optimization with applications to robotic model and image recoveryNasiru SalihuPoom KumamAliyu Muhammed AwwalIbrahim Mohammed SulaimanThidaporn Seangwattana10.1371/journal.pone.02812502023-03-16T14:00:00Z2023-03-16T14:00:00Z<p>by Nasiru Salihu, Poom Kumam, Aliyu Muhammed Awwal, Ibrahim Mohammed Sulaiman, Thidaporn Seangwattana</p>
In 2012, Rivaie et al. introduced RMIL conjugate gradient (CG) method which is globally convergent under the exact line search. Later, Dai (2016) pointed out abnormality in the convergence result and thus, imposed certain restricted RMIL CG parameter as a remedy. In this paper, we suggest an efficient RMIL spectral CG method. The remarkable feature of this method is that, the convergence result is free from additional condition usually imposed on RMIL. Subsequently, the search direction is sufficiently descent independent of any line search technique. Thus, numerical experiments on some set of benchmark problems indicate that the method is promising and efficient. Furthermore, the efficiency of the proposed method is demonstrated on applications arising from arm robotic model and image restoration problems.A framework for macroscopic phase-resetting curves for generalised spiking neural networksGrégory DumontAlberto Pérez-CerveraBoris Gutkin10.1371/journal.pcbi.10103632022-08-01T14:00:00Z2022-08-01T14:00:00Z<p>by Grégory Dumont, Alberto Pérez-Cervera, Boris Gutkin</p>
Brain rhythms emerge from synchronization among interconnected spiking neurons. Key properties of such rhythms can be gleaned from the phase-resetting curve (PRC). Inferring the PRC and developing a systematic phase reduction theory for large-scale brain rhythms remains an outstanding challenge. Here we present a theoretical framework and methodology to compute the PRC of generic spiking networks with emergent collective oscillations. We adopt a renewal approach where neurons are described by the time since their last action potential, a description that can reproduce the dynamical feature of many cell types. For a sufficiently large number of neurons, the network dynamics are well captured by a continuity equation known as the refractory density equation. We develop an adjoint method for this equation giving a semi-analytical expression of the infinitesimal PRC. We confirm the validity of our framework for specific examples of neural networks. Our theoretical framework can link key biological properties at the individual neuron scale and the macroscopic oscillatory network properties. Beyond spiking networks, the approach is applicable to a broad class of systems that can be described by renewal processes.A direct comparison of theory-driven and machine learning prediction of suicide: A meta-analysisKatherine M. SchaferGrace KennedyAustin GallyerPhilip Resnik10.1371/journal.pone.02498332021-04-12T14:00:00Z2021-04-12T14:00:00Z<p>by Katherine M. Schafer, Grace Kennedy, Austin Gallyer, Philip Resnik</p>
Theoretically-driven models of suicide have long guided suicidology; however, an approach employing machine learning models has recently emerged in the field. Some have suggested that machine learning models yield improved prediction as compared to theoretical approaches, but to date, this has not been investigated in a systematic manner. The present work directly compares widely researched theories of suicide (<i>i</i>.<i>e</i>., BioSocial, Biological, Ideation-to-Action, and Hopelessness Theories) to machine learning models, comparing the accuracy between the two differing approaches. We conducted literature searches using PubMed, PsycINFO, and Google Scholar, gathering effect sizes from theoretically-relevant constructs and machine learning models. Eligible studies were longitudinal research articles that predicted suicide ideation, attempts, or death published prior to May 1, 2020. 124 studies met inclusion criteria, corresponding to 330 effect sizes. Theoretically-driven models demonstrated suboptimal prediction of ideation (wOR = 2.87; 95% CI, 2.65–3.09; <i>k</i> = 87), attempts (wOR = 1.43; 95% CI, 1.34–1.51; <i>k</i> = 98), and death (wOR = 1.08; 95% CI, 1.01–1.15; <i>k</i> = 78). Generally, Ideation-to-Action (<i>w</i>OR = 2.41, 95% CI = 2.21–2.64, <i>k</i> = 60) outperformed Hopelessness (<i>w</i>OR = 1.83, 95% CI 1.71–1.96, <i>k</i> = 98), Biological (<i>w</i>OR = 1.04; 95% CI .97–1.11, <i>k</i> = 100), and BioSocial (<i>w</i>OR = 1.32, 95% CI 1.11–1.58, <i>k</i> = 6) theories. Machine learning provided superior prediction of ideation (wOR = 13.84; 95% CI, 11.95–16.03; <i>k</i> = 33), attempts (wOR = 99.01; 95% CI, 68.10–142.54; <i>k</i> = 27), and death (wOR = 17.29; 95% CI, 12.85–23.27; <i>k</i> = 7). Findings from our study indicated that across all theoretically-driven models, prediction of suicide-related outcomes was suboptimal. Notably, among theories of suicide, theories within the Ideation-to-Action framework provided the most accurate prediction of suicide-related outcomes. When compared to theoretically-driven models, machine learning models provided superior prediction of suicide ideation, attempts, and death.Testing structural identifiability by a simple scaling methodMario CastroRob J. de Boer10.1371/journal.pcbi.10082482020-11-03T14:00:00Z2020-11-03T14:00:00Z<p>by Mario Castro, Rob J. de Boer</p>
Successful mathematical modeling of biological processes relies on the expertise of the modeler to capture the essential mechanisms in the process at hand and on the ability to extract useful information from empirical data. A model is said to be structurally unidentifiable, if different quantitative sets of parameters provide the same observable outcome. This is typical (but not exclusive) of partially observed problems in which only a few variables can be experimentally measured. Most of the available methods to test the structural identifiability of a model are either too complex mathematically for the general practitioner to be applied, or require involved calculations or numerical computation for complex non-linear models. In this work, we present a new analytical method to test structural identifiability of models based on ordinary differential equations, based on the invariance of the equations under the scaling transformation of its parameters. The method is based on rigorous mathematical results but it is easy and quick to apply, even to test the identifiability of sophisticated highly non-linear models. We illustrate our method by example and compare its performance with other existing methods in the literature.Request a woman scientist: A database for diversifying the public face of scienceElizabeth A. McCullaghKatarzyna NowakAnne PogorilerJessica L. MetcalfMaryam ZaringhalamT. Jane Zelikova10.1371/journal.pbio.30002122019-04-23T14:00:00Z2019-04-23T14:00:00Z<p>by Elizabeth A. McCullagh, Katarzyna Nowak, Anne Pogoriler, Jessica L. Metcalf, Maryam Zaringhalam, T. Jane Zelikova</p>
A global online register of women scientists, ready to share their science, was established by a cohort of volunteer women from the grassroots organization 500 Women Scientists on January 17th, 2018. In less than one year, the database “Request a Woman Scientist” comprised over 7,500 women from 174 scientific disciplines and 133 countries. The database is built upon a voluntary questionnaire regarding career stage, degree, scientific discipline, geographic location, and other self-identifying dimensions of representation. The information was visualized using the software platform Tableau, with dropdown menus that help query the database and output a list of names, email addresses, and websites. The biological sciences and women scientists from the United States of America were best represented in the database. A survey of women in the database conducted in November 2018 showed that of 1,278 respondents, 11% had been contacted since signing up for a variety of engagements, including media, peer review, panel participation, educational outreach, and professional/research connections. These engagements resulted in consultations for articles, video chats with students, and speaking opportunities at conferences and events. With improved functionality and marketing, outreach in the global south, and future translation in other languages, this database will further promote the profile and participation of women scientists across society, which in turn will benefit the advancement of science.Oscillatory dynamics in a discrete predator-prey model with distributed delaysChangjin XuLilin ChenPeiluan LiYing Guo10.1371/journal.pone.02083222018-12-26T14:00:00Z2018-12-26T14:00:00Z<p>by Changjin Xu, Lilin Chen, Peiluan Li, Ying Guo</p>
This work aims to discuss a predator-prey system with distributed delay. Various conditions are presented to ensure the existence and global asymptotic stability of positive periodic solution of the involved model. The method is based on coincidence degree theory and the idea of Lyapunov function. At last, simulation results are presented to show the correctness of theoretical findings.Limits on reliable information flows through stochastic populationsLucas BoczkowskiEmanuele NataleOfer FeinermanAmos Korman10.1371/journal.pcbi.10061952018-06-06T14:00:00Z2018-06-06T14:00:00Z<p>by Lucas Boczkowski, Emanuele Natale, Ofer Feinerman, Amos Korman</p>
Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic collective task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. We study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this task. We present an impossibility result which strongly restricts reliable rumor spreading in such groups. Namely, we prove that, in the presence of even moderate levels of noise that affect all facets of the communication, no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources—a process which requires linear time in the population size. Our results imply that in order to achieve efficient rumor spread a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We then corroborate this claim by providing new analyses of experimental data regarding recruitment in <i>Cataglyphis niger</i> desert ants. Finally, in light of our theoretical results, we discuss strategies to overcome noise in other biological systems.A quantitative evaluation of multiple biokinetic models using an assembled water phantom: A feasibility studyDa-Ming YehChing-Yuan ChenJing-Fa TangLung-Kwang Pan10.1371/journal.pone.01892442017-12-21T14:00:00Z2017-12-21T14:00:00Z<p>by Da-Ming Yeh, Ching-Yuan Chen, Jing-Fa Tang, Lung-Kwang Pan</p>
This study examined the feasibility of quantitatively evaluating multiple biokinetic models and established the validity of the different compartment models using an assembled water phantom. Most commercialized phantoms are made to survey the imaging system since this is essential to increase the diagnostic accuracy for quality assurance. In contrast, few customized phantoms are specifically made to represent multi-compartment biokinetic models. This is because the complicated calculations as defined to solve the biokinetic models and the time-consuming verifications of the obtained solutions are impeded greatly the progress over the past decade. Nevertheless, in this work, five biokinetic models were separately defined by five groups of simultaneous differential equations to obtain the time-dependent radioactive concentration changes inside the water phantom. The water phantom was assembled by seven acrylic boxes in four different sizes, and the boxes were linked to varying combinations of hoses to signify the multiple biokinetic models from the biomedical perspective. The boxes that were connected by hoses were then regarded as a closed water loop with only one infusion and drain. 129.1±24.2 MBq of Tc-99m labeled methylene diphosphonate (MDP) solution was thoroughly infused into the water boxes before gamma scanning; then the water was replaced with de-ionized water to simulate the biological removal rate among the boxes. The water was driven by an automatic infusion pump at 6.7 c.c./min, while the biological half-life of the four different-sized boxes (64, 144, 252, and 612 c.c.) was 4.8, 10.7, 18.8, and 45.5 min, respectively. The five models of derived time-dependent concentrations for the boxes were estimated either by a self-developed program run in MATLAB or by scanning via a gamma camera facility. Either agreement or disagreement between the practical scanning and the theoretical prediction in five models was thoroughly discussed. The derived biokinetic model represented the metabolic mechanism in the human body and helped to solidify the internal circulatory system into concert with numerical verification.Some Agreement on Kin Selection and Eusociality?David C. QuellerStephen RongXiaoyun Liao10.1371/journal.pbio.10021332015-04-24T14:00:00Z2015-04-24T14:00:00Z<p>by David C. Queller, Stephen Rong, Xiaoyun Liao</p>
The authors of "Relatedness, Conflict, and the Evolution of Eusociality" respond to objections raised by Martin Nowak and Benjamin Allen.How to Write a Presubmission InquiryThomas LengauerRuth Nussinov10.1371/journal.pcbi.10040982015-02-26T14:00:00Z2015-02-26T14:00:00Z<p>by Thomas Lengauer, Ruth Nussinov</p>Exact Solutions of Linear Reaction-Diffusion Processes on a Uniformly Growing Domain: Criteria for Successful ColonizationMatthew J Simpson10.1371/journal.pone.01179492015-02-18T14:00:00Z2015-02-18T14:00:00Z<p>by Matthew J Simpson</p>
Many processes during embryonic development involve transport and reaction of molecules, or transport and proliferation of cells, within growing tissues. Mathematical models of such processes usually take the form of a reaction-diffusion partial differential equation (PDE) on a growing domain. Previous analyses of such models have mainly involved solving the PDEs numerically. Here, we present a framework for calculating the exact solution of a linear reaction-diffusion PDE on a growing domain. We derive an exact solution for a general class of one-dimensional linear reaction—diffusion process on 0<<i>x</i><<i>L</i>(<i>t</i>), where <i>L</i>(<i>t</i>) is the length of the growing domain. Comparing our exact solutions with numerical approximations confirms the veracity of the method. Furthermore, our examples illustrate a delicate interplay between: (i) the rate at which the domain elongates, (ii) the diffusivity associated with the spreading density profile, (iii) the reaction rate, and (iv) the initial condition. Altering the balance between these four features leads to different outcomes in terms of whether an initial profile, located near <i>x</i> = 0, eventually overcomes the domain growth and colonizes the entire length of the domain by reaching the boundary where <i>x</i> = <i>L</i>(<i>t</i>).The Role of Opportunistic Migration in Cyclic GamesPierre BuesserMarco Tomassini10.1371/journal.pone.00981902014-06-03T14:00:00Z2014-06-03T14:00:00Z<p>by Pierre Buesser, Marco Tomassini</p>
We study cyclic evolutionary games in a spatial diluted grid environment in which agents strategically interact locally but can also opportunistically move to other positions within a given migration radius. We find that opportunistic migration can inverse the cyclic prevalence between the strategies when the frequency of random imitation is large enough compared to the payoff-driven imitation. At the transition the average size of the patterns diverges and this threatens diversity of strategies.Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts ModelAnja Voss-Böhme10.1371/journal.pone.00428522012-09-11T14:00:00Z2012-09-11T14:00:00Z<p>by Anja Voss-Böhme</p>
Cellular Potts models (CPMs) are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model. While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model.