Pub Date : 2021-02-17DOI: 10.30707/LiB8.1.1647878866.083342
Sherli Koshy-Chenthittayil, Pedro Mendes, Reinhard Laubenbacher
Optimization and control are important objectives across biology and biomedicine, and mathematical models are a key enabling technology. This paper reports a computational study of model-based multi-objective optimization in the setting of microbial ecology, using agent-based models. This modeling framework is well-suited to the field, but is not amenable to standard control-theoretic approaches. Furthermore, due to computational complexity, simulation-based optimization approaches are often challenging to implement. This paper presents the results of an approach that combines control-dependent coarse-graining with Pareto optimization, applied to two models of multi-species bacterial biofilms. It shows that this approach can be successful for models whose computational complexity prevents effective simulation-based optimization.
{"title":"Optimization of Agent-Based Models Through Coarse-Graining: A Case Study in Microbial Ecology.","authors":"Sherli Koshy-Chenthittayil, Pedro Mendes, Reinhard Laubenbacher","doi":"10.30707/LiB8.1.1647878866.083342","DOIUrl":"https://doi.org/10.30707/LiB8.1.1647878866.083342","url":null,"abstract":"<p><p>Optimization and control are important objectives across biology and biomedicine, and mathematical models are a key enabling technology. This paper reports a computational study of model-based multi-objective optimization in the setting of microbial ecology, using agent-based models. This modeling framework is well-suited to the field, but is not amenable to standard control-theoretic approaches. Furthermore, due to computational complexity, simulation-based optimization approaches are often challenging to implement. This paper presents the results of an approach that combines control-dependent coarse-graining with Pareto optimization, applied to two models of multi-species bacterial biofilms. It shows that this approach can be successful for models whose computational complexity prevents effective simulation-based optimization.</p>","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":"8 1","pages":"167-178"},"PeriodicalIF":0.0,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9802647/pdf/nihms-1856101.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10476536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Boris Aguilar, Pan Fang, Reinhard Laubenbacher, David Murrugarra
One of the ultimate goals in systems biology is to develop control strategies to find efficient medical treatments. One step towards this goal is to develop methods for changing the state of a cell into a desirable state. We propose an efficient method that determines combinations of network perturbations to direct the system towards a predefined state. The method requires a set of control actions such as the silencing of a gene or the disruption of the interaction between two genes. An optimal control policy defined as the best intervention at each state of the system can be obtained using existing methods. However, these algorithms are computationally prohibitive for models with tens of nodes. Our method generates control actions that approximates the optimal control policy with high probability with a computational efficiency that does not depend on the size of the state space. Our C++ code is available at https://github.com/boaguilar/SDDScontrol.
{"title":"A Near-Optimal Control Method for Stochastic Boolean Networks.","authors":"Boris Aguilar, Pan Fang, Reinhard Laubenbacher, David Murrugarra","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>One of the ultimate goals in systems biology is to develop control strategies to find efficient medical treatments. One step towards this goal is to develop methods for changing the state of a cell into a desirable state. We propose an efficient method that determines combinations of network perturbations to direct the system towards a predefined state. The method requires a set of control actions such as the silencing of a gene or the disruption of the interaction between two genes. An optimal control policy defined as the best intervention at each state of the system can be obtained using existing methods. However, these algorithms are computationally prohibitive for models with tens of nodes. Our method generates control actions that approximates the optimal control policy with high probability with a computational efficiency that does not depend on the size of the state space. Our C++ code is available at https://github.com/boaguilar/SDDScontrol.</p>","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":"7 1","pages":"67-80"},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208226/pdf/nihms-1704776.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39243403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-04DOI: 10.1080/23737867.2019.1685920
A. Kaur, K. Funderburk, A. Campaña, P. Puente, Karen Ríos-Soto
Asthma is a chronic respiratory condition which affects 25 million people in the United States. Improper extermination of cockroaches and their associated allergens significantly increases the occurrence of atopic asthma, a type of asthma stemming from exposure to allergens. To date, dynamical studies of cockroach infestations and their effects on atopic asthma have not been examined. Here we develop a novel mathematical model, with households as the model unit, to study the dynamics of cockroach infestations within a neighbourhood and how they impact the prevalence of asthma. The focus of this study is to evaluate the impact of extermination and removal of allergens in a household containing an individual with recurrent atopic asthma. Through analysing our model, the basic reproduction number for cockroach infestations was calculated and we were able to determine conditions under which cockroaches and asthma can be eliminated from a community containing infested houses. From the presence of a backward bifurcation, we are able to show that it is
{"title":"A Household Model of German Cockroach Infestations and Their Effects on Symptoms of Atopic Asthma","authors":"A. Kaur, K. Funderburk, A. Campaña, P. Puente, Karen Ríos-Soto","doi":"10.1080/23737867.2019.1685920","DOIUrl":"https://doi.org/10.1080/23737867.2019.1685920","url":null,"abstract":"Asthma is a chronic respiratory condition which affects 25 million people in the United States. Improper extermination of cockroaches and their associated allergens significantly increases the occurrence of atopic asthma, a type of asthma stemming from exposure to allergens. To date, dynamical studies of cockroach infestations and their effects on atopic asthma have not been examined. Here we develop a novel mathematical model, with households as the model unit, to study the dynamics of cockroach infestations within a neighbourhood and how they impact the prevalence of asthma. The focus of this study is to evaluate the impact of extermination and removal of allergens in a household containing an individual with recurrent atopic asthma. Through analysing our model, the basic reproduction number for cockroach infestations was calculated and we were able to determine conditions under which cockroaches and asthma can be eliminated from a community containing infested houses. From the presence of a backward bifurcation, we are able to show that it is","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1685920","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44615076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-24DOI: 10.1080/23737867.2019.1653234
R. Mayes, Kent Rittschof, J. Dauer, Bryon Gallant
The Quantitative Modelling Biology Undergraduate Assessment (QM BUGS Version II) assesses undergraduate biology students’ quantitative modelling abilities and confidence. The assessment is intended...
定量建模生物学本科评估(QM BUGS Version II)评估生物学本科学生的定量建模能力和信心。评估的目的是…
{"title":"Quantitative Modelling Biology Undergraduate Assessment","authors":"R. Mayes, Kent Rittschof, J. Dauer, Bryon Gallant","doi":"10.1080/23737867.2019.1653234","DOIUrl":"https://doi.org/10.1080/23737867.2019.1653234","url":null,"abstract":"The Quantitative Modelling Biology Undergraduate Assessment (QM BUGS Version II) assesses undergraduate biology students’ quantitative modelling abilities and confidence. The assessment is intended...","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1653234","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44597065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-24DOI: 10.1080/23737867.2019.1654418
Sarada Ghosh, G. Samanta
This study involves statistical analysis of reported cases of sexually transmitted diseases (STDs) of Chlamydia infection in the United States. The data are collected from 2007 to 2016. The researc...
{"title":"Model Justification and Stratification for Confounding of Chlamydia Trachomatis Disease","authors":"Sarada Ghosh, G. Samanta","doi":"10.1080/23737867.2019.1654418","DOIUrl":"https://doi.org/10.1080/23737867.2019.1654418","url":null,"abstract":"This study involves statistical analysis of reported cases of sexually transmitted diseases (STDs) of Chlamydia infection in the United States. The data are collected from 2007 to 2016. The researc...","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1654418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46998812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-24DOI: 10.1080/23737867.2019.1656562
M. Rivera-Castro, P. Padmanabhan, C. Caiseda, P. Seshaiyer, C. Boria-Guanill
Youth that live in public housing communities with high social and financial needs are at risk of getting involved in illegal drug trafficking gangs that are controlled by adults. This social disea...
{"title":"Mathematical Modelling, Analysis and Simulation of the Spread of Gangs in Interacting Youth and Adult Populations","authors":"M. Rivera-Castro, P. Padmanabhan, C. Caiseda, P. Seshaiyer, C. Boria-Guanill","doi":"10.1080/23737867.2019.1656562","DOIUrl":"https://doi.org/10.1080/23737867.2019.1656562","url":null,"abstract":"Youth that live in public housing communities with high social and financial needs are at risk of getting involved in illegal drug trafficking gangs that are controlled by adults. This social disea...","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1656562","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44604187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-23DOI: 10.1080/23737867.2019.1618743
P. Danumjaya, Merina Dhara
In this article, we study the non-standard finite difference (NSFD) schemes for the diabetes mellitus with tuberculosis infection. We have classified diabetes mellitus into two categories such as d...
{"title":"Stability Preserving Non-Standard Finite Difference Schemes for Diabetes with Tuberculosis Infectious Model","authors":"P. Danumjaya, Merina Dhara","doi":"10.1080/23737867.2019.1618743","DOIUrl":"https://doi.org/10.1080/23737867.2019.1618743","url":null,"abstract":"In this article, we study the non-standard finite difference (NSFD) schemes for the diabetes mellitus with tuberculosis infection. We have classified diabetes mellitus into two categories such as d...","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1618743","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43500789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-05-23DOI: 10.1080/23737867.2019.1618744
Subekshya Bidari, Eli E. Goldwyn
Disease outbreaks on residential college campuses provide an ideal opportunity for mathematical modelling. Unfortunately, publicly available data are rare and many of these outbreaks are relatively small, confounding traditional data-fitting techniques such as least-squares. Using data from three outbreaks during the 2015 and 2017 flu seasons at Trinity College, we fit several SIR-type stochastic models by approximating the likelihood of each model. We find that stochasticity is a key driver in determining the size of the outbreak, and that it strongly depends on the amount of time between the start of the outbreak and the next school holiday. Our results indicate that in order to prevent or limit the size of an outbreak, school closure is likely to be more effective than increasing the vaccination rate. As influenza is a leading cause of negative academic outcomes, these results offer important guidance for school administrators.
{"title":"Stochastic Models of Influenza Outbreaks on a College Campus","authors":"Subekshya Bidari, Eli E. Goldwyn","doi":"10.1080/23737867.2019.1618744","DOIUrl":"https://doi.org/10.1080/23737867.2019.1618744","url":null,"abstract":"Disease outbreaks on residential college campuses provide an ideal opportunity for mathematical modelling. Unfortunately, publicly available data are rare and many of these outbreaks are relatively small, confounding traditional data-fitting techniques such as least-squares. Using data from three outbreaks during the 2015 and 2017 flu seasons at Trinity College, we fit several SIR-type stochastic models by approximating the likelihood of each model. We find that stochasticity is a key driver in determining the size of the outbreak, and that it strongly depends on the amount of time between the start of the outbreak and the next school holiday. Our results indicate that in order to prevent or limit the size of an outbreak, school closure is likely to be more effective than increasing the vaccination rate. As influenza is a leading cause of negative academic outcomes, these results offer important guidance for school administrators.","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1618744","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43857377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-12DOI: 10.1080/23737867.2019.1585981
N. Mukherjee, S. Ghorai, M. Banerjee
Pattern formation is widely studied in spatio-temporal prey– predator models with only self-diffusion terms. Models with cross-diffusion, besides self-diffusion, take care of the situation in which...
模式形成在只有自扩散项的时空食饵-捕食者模型中得到了广泛的研究。除自扩散外，交叉扩散模型还考虑了…
{"title":"Cross-Diffusion Induced Turing and non-Turing Patterns in Rosenzweig–MacArthur Model","authors":"N. Mukherjee, S. Ghorai, M. Banerjee","doi":"10.1080/23737867.2019.1585981","DOIUrl":"https://doi.org/10.1080/23737867.2019.1585981","url":null,"abstract":"Pattern formation is widely studied in spatio-temporal prey– predator models with only self-diffusion terms. Models with cross-diffusion, besides self-diffusion, take care of the situation in which...","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1585981","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47536964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.1080/23737867.2019.1691946
H. Yoshioka, Y. Yaegashi, Y. Yoshioka, Kentaro Tsugihashi
ABSTRACT A minimal stochastic generalization of a deterministic open-ended logistic growth model is proposed for efficiently describing the biological growth of individual organisms under natural environment. The model is a system of stochastic differential equations. Its unique solvability in a strong sense is proven, and the behaviour of the solution is analysed. The presented model is then applied to the migratory fish Plecoglossus altivelis altivelis (P. altivelis, Ayu) having a one-year life history based on the data sets collected in 2017 and 2018.
{"title":"A short note on analysis and application of a stochastic open-ended logistic growth model","authors":"H. Yoshioka, Y. Yaegashi, Y. Yoshioka, Kentaro Tsugihashi","doi":"10.1080/23737867.2019.1691946","DOIUrl":"https://doi.org/10.1080/23737867.2019.1691946","url":null,"abstract":"ABSTRACT A minimal stochastic generalization of a deterministic open-ended logistic growth model is proposed for efficiently describing the biological growth of individual organisms under natural environment. The model is a system of stochastic differential equations. Its unique solvability in a strong sense is proven, and the behaviour of the solution is analysed. The presented model is then applied to the migratory fish Plecoglossus altivelis altivelis (P. altivelis, Ayu) having a one-year life history based on the data sets collected in 2017 and 2018.","PeriodicalId":37222,"journal":{"name":"Letters in Biomathematics","volume":"6 1","pages":"67 - 77"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23737867.2019.1691946","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42503165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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