Physical biology最新文献_第10页

Learning feedback molecular network models using integer linear programming. 利用整数线性规划学习反馈分子网络模型。

IF 2 4区生物学

Physical biology Pub Date : 2022-10-04 DOI: 10.1088/1478-3975/ac920d

Mustafa Ozen, Effat S Emamian, Ali Abdi

{"title":"Learning feedback molecular network models using integer linear programming.","authors":"Mustafa Ozen, Effat S Emamian, Ali Abdi","doi":"10.1088/1478-3975/ac920d","DOIUrl":"https://doi.org/10.1088/1478-3975/ac920d","url":null,"abstract":"Analysis of intracellular molecular networks has many applications in understanding of the molecular bases of some complex diseases and finding effective therapeutic targets for drug development. To perform such analyses, the molecular networks need to be converted into computational models. In general, network models constructed using literature and pathway databases may not accurately predict experimental network data. This can be due to the incompleteness of literature on molecular pathways, the resources used to construct the networks, or some conflicting information in the resources. In this paper, we propose a network learning approach via an integer linear programming formulation that can systematically incorporate biological dynamics and regulatory mechanisms of molecular networks in the learning process. Moreover, we present a method to properly consider the feedback paths, while learning the network from data. Examples are also provided to show how one can apply the proposed learning approach to a network of interest. In particular, we apply the framework to the ERBB signaling network, to learn it from some experimental data. Overall, the proposed methods are useful for reducing the gap between the curated networks and experimental data, and result in calibrated networks that are more reliable for making biologically meaningful predictions.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40357335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comment on 'A physics perspective on collective animal behavior' 2022Phys. Biol.19 021004. 评论“集体动物行为的物理学视角”2022Phys。Biol.19 021004。

IF 2 4区生物学

Physical biology Pub Date : 2022-09-19 DOI: 10.1088/1478-3975/ac8fd5

Andy M Reynolds

引用次数: 2

A compressed logistic equation on bacteria growth: inferring time-dependent growth rate. 细菌生长的压缩逻辑方程:推断随时间变化的生长速率。

IF 2 4区生物学

Physical biology Pub Date : 2022-09-15 DOI: 10.1088/1478-3975/ac8c15

Carlito Pinto, Koichi Shimakawa

引用次数: 3

Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology. 重构细胞表型转换的数据驱动管理方程：数据科学与系统生物学的整合。

IF 2 4区生物学

Physical biology Pub Date : 2022-09-09 DOI: 10.1088/1478-3975/ac8c16

Jianhua Xing

{"title":"Reconstructing data-driven governing equations for cell phenotypic transitions: integration of data science and systems biology.","authors":"Jianhua Xing","doi":"10.1088/1478-3975/ac8c16","DOIUrl":"10.1088/1478-3975/ac8c16","url":null,"abstract":"Cells with the same genome can exist in different phenotypes and can change between distinct phenotypes when subject to specific stimuli and microenvironments. Some examples include cell differentiation during development, reprogramming for induced pluripotent stem cells and transdifferentiation, cancer metastasis and fibrosis progression. The regulation and dynamics of cell phenotypic conversion is a fundamental problem in biology, and has a long history of being studied within the formalism of dynamical systems. A main challenge for mechanism-driven modeling studies is acquiring sufficient amount of quantitative information for constraining model parameters. Advances in quantitative experimental approaches, especially high throughput single-cell techniques, have accelerated the emergence of a new direction for reconstructing the governing dynamical equations of a cellular system from quantitative single-cell data, beyond the dominant statistical approaches. Here I review a selected number of recent studies using live- and fixed-cell data and provide my perspective on future development.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"19 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9585661/pdf/nihms-1835862.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10557945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-genetic resistance facilitates survival while hindering the evolution of drug resistance due to intraspecific competition. 非遗传抗性促进了生存，同时由于种内竞争阻碍了耐药性的进化。

IF 2 4区生物学

Physical biology Pub Date : 2022-09-08 DOI: 10.1088/1478-3975/ac8c17

Joshua D Guthrie, Daniel A Charlebois

{"title":"Non-genetic resistance facilitates survival while hindering the evolution of drug resistance due to intraspecific competition.","authors":"Joshua D Guthrie, Daniel A Charlebois","doi":"10.1088/1478-3975/ac8c17","DOIUrl":"https://doi.org/10.1088/1478-3975/ac8c17","url":null,"abstract":"Rising rates of resistance to antimicrobial drugs threaten the effective treatment of infections across the globe. Drug resistance has been established to emerge from non-genetic mechanisms as well as from genetic mechanisms. However, it is still unclear how non-genetic resistance affects the evolution of genetic drug resistance. We develop deterministic and stochastic population models that incorporate resource competition to quantitatively investigate the transition from non-genetic to genetic resistance during the exposure to static and cidal drugs. We find that non-genetic resistance facilitates the survival of cell populations during drug treatment while hindering the development of genetic resistance due to competition between the non-genetically and genetically resistant subpopulations. Non-genetic resistance in the presence of subpopulation competition increases the fixation times of drug resistance mutations, while increasing the probability of mutation before population extinction during cidal drug treatment. Intense intraspecific competition during drug treatment leads to extinction of susceptible and non-genetically resistant subpopulations. Alternating between drug and no drug conditions results in oscillatory population dynamics, increased resistance mutation fixation timescales, and reduced population survival. These findings advance our fundamental understanding of the evolution of resistance and may guide novel treatment strategies for patients with drug-resistant infections.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40436958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Long-range morphogen gradient formation by cell-to-cell signal propagation. 细胞间信号传播形成的远距离形态形成梯度。

IF 2 4区生物学

Physical biology Pub Date : 2022-09-07 DOI: 10.1088/1478-3975/ac86b4

Johanna E M Dickmann, Jochen C Rink, Frank Jülicher

{"title":"Long-range morphogen gradient formation by cell-to-cell signal propagation.","authors":"Johanna E M Dickmann, Jochen C Rink, Frank Jülicher","doi":"10.1088/1478-3975/ac86b4","DOIUrl":"https://doi.org/10.1088/1478-3975/ac86b4","url":null,"abstract":"Morphogen gradients are a central concept in developmental biology. Their formation often involves the secretion of morphogens from a local source, that spread by diffusion in the cell field, where molecules eventually get degraded. This implies limits to both the time and length scales over which morphogen gradients can form which are set by diffusion coefficients and degradation rates. Towards the goal of identifying plausible mechanisms capable of extending the gradient range, we here use theory to explore properties of a cell-to-cell signaling relay. Inspired by the millimeter-scalewnt-expression and signaling gradients in flatworms, we consider morphogen-mediated morphogen production in the cell field. We show that such a relay can generate stable morphogen and signaling gradients that are oriented by a local, morphogen-independent source of morphogen at a boundary. This gradient formation can be related to an effective diffusion and an effective degradation that result from morphogen production due to signaling relay. If the secretion of morphogen produced in response to the relay is polarized, it further gives rise to an effective drift. We find that signaling relay can generate long-range gradients in relevant times without relying on extreme choices of diffusion coefficients or degradation rates, thus exceeding the limits set by physiological diffusion coefficients and degradation rates. A signaling relay is hence an attractive principle to conceptualize long-range gradient formation by slowly diffusing morphogens that are relevant for patterning in adult contexts such as regeneration and tissue turn-over.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40580475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Nonparametric Bayesian inference for meta-stable conformational dynamics. 亚稳定构象动力学的非参数贝叶斯推理。

IF 2 4区生物学

Physical biology Pub Date : 2022-08-30 DOI: 10.1088/1478-3975/ac885e

Lukas Köhs, Kerri Kukovetz, Oliver Rauh, Heinz Koeppl

{"title":"Nonparametric Bayesian inference for meta-stable conformational dynamics.","authors":"Lukas Köhs, Kerri Kukovetz, Oliver Rauh, Heinz Koeppl","doi":"10.1088/1478-3975/ac885e","DOIUrl":"https://doi.org/10.1088/1478-3975/ac885e","url":null,"abstract":"Analyses of structural dynamics of biomolecules hold great promise to deepen the understanding of and ability to construct complex molecular systems. To this end, both experimental and computational means are available, such as fluorescence quenching experiments or molecular dynamics simulations, respectively. We argue that while seemingly disparate, both fields of study have to deal with the same type of data about the same underlying phenomenon of conformational switching. Two central challenges typically arise in both contexts: (i) the amount of obtained data is large, and (ii) it is often unknown how many distinct molecular states underlie these data. In this study, we build on the established idea of Markov state modeling and propose a generative, Bayesian nonparametric hidden Markov state model that addresses these challenges. Utilizing hierarchical Dirichlet processes, we treat different meta-stable molecule conformations as distinct Markov states, the number of which we then do not have to seta priori. In contrast to existing approaches to both experimental as well as simulation data that are based on the same idea, we leverage a mean-field variational inference approach, enabling scalable inference on large amounts of data. Furthermore, we specify the model also for the important case of angular data, which however proves to be computationally intractable. Addressing this issue, we propose a computationally tractable approximation to the angular model. We demonstrate the method on synthetic ground truth data and apply it to known benchmark problems as well as electrophysiological experimental data from a conformation-switching ion channel to highlight its practical utility.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40598172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Growth instabilities shape morphology and genetic diversity of microbial colonies. 生长不稳定性决定了微生物菌落的形态和遗传多样性。

IF 2 4区生物学

Physical biology Pub Date : 2022-08-19 DOI: 10.1088/1478-3975/ac8514

Alexander Golden, Ilija Dukovski, Daniel Segrè, Kirill S Korolev

{"title":"Growth instabilities shape morphology and genetic diversity of microbial colonies.","authors":"Alexander Golden, Ilija Dukovski, Daniel Segrè, Kirill S Korolev","doi":"10.1088/1478-3975/ac8514","DOIUrl":"10.1088/1478-3975/ac8514","url":null,"abstract":"Cellular populations assume an incredible variety of shapes ranging from circular molds to irregular tumors. While we understand many of the mechanisms responsible for these spatial patterns, little is known about how the shape of a population influences its ecology and evolution. Here, we investigate this relationship in the context of microbial colonies grown on hard agar plates. This a well-studied system that exhibits a transition from smooth circular disks to more irregular and rugged shapes as either the nutrient concentration or cellular motility is decreased. Starting from a mechanistic model of colony growth, we identify two dimensionless quantities that determine how morphology and genetic diversity of the population depend on the model parameters. Our simulations further reveal that population dynamics cannot be accurately described by the commonly-used surface growth models. Instead, one has to explicitly account for the emergent growth instabilities and demographic fluctuations. Overall, our work links together environmental conditions, colony morphology, and evolution. This link is essential for a rational design of concrete, biophysical perturbations to steer evolution in the desired direction.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11209841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40570732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The role of spatial structures of tissues in cancer initiation dynamics. 组织空间结构在癌变起始动力学中的作用。

IF 2 4区生物学

Physical biology Pub Date : 2022-08-18 DOI: 10.1088/1478-3975/ac8515

Cade Spaulding, Hamid Teimouri, Anatoly B Kolomeisky

{"title":"The role of spatial structures of tissues in cancer initiation dynamics.","authors":"Cade Spaulding, Hamid Teimouri, Anatoly B Kolomeisky","doi":"10.1088/1478-3975/ac8515","DOIUrl":"https://doi.org/10.1088/1478-3975/ac8515","url":null,"abstract":"It is widely believed that biological tissues evolved to lower the risks of cancer development. One of the specific ways to minimize the chances of tumor formation comes from proper spatial organization of tissues. However, the microscopic mechanisms of underlying processes remain not fully understood. We present a theoretical investigation on the role of spatial structures in cancer initiation dynamics. In our approach, the dynamics of single mutation fixations are analyzed using analytical calculations and computer simulations by mapping them to Moran processes on graphs with different connectivity that mimic various spatial structures. It is found that while the fixation probability is not affected by modifying the spatial structures of the tissues, the fixation times can change dramatically. The slowest dynamics is observed in 'quasi-one-dimensional' structures, while the fastest dynamics is observed in 'quasi-three-dimensional' structures. Theoretical calculations also suggest that there is a critical value of the degree of graph connectivity, which mimics the spatial dimension of the tissue structure, above which the spatial structure of the tissue has no effect on the mutation fixation dynamics. An effective discrete-state stochastic model of cancer initiation is utilized to explain our theoretical results and predictions. Our theoretical analysis clarifies some important aspects on the role of the tissue spatial structures in the cancer initiation processes.","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40570734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Modeling the dynamics of innate immune response to Parkinson disease with therapeutic approach. 用治疗方法模拟先天免疫反应对帕金森病的动力学。

IF 2 4区生物学

Physical biology Pub Date : 2022-08-18 DOI: 10.1088/1478-3975/ac8516

Asma Badrah, Salma Al-Tuwairqi

引用次数: 1