Markov State Models of gene regulatory networks
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- 作者：Brian K. Chu ; Margaret J. Tse ; Royce R. Sato ; Elizabeth L. Read
- 关键词：Multistable systems ; Stochastic processes ; Gene regulatory networks ; Markov State Models ; Cluster analysis
- 刊名：BMC Systems Biology
- 出版年：2017
- 出版时间：December 2017
- 年：2017
- 卷：11
- 期：1
- 全文大小：3777KB
- 刊物主题：Bioinformatics; Systems Biology; Simulation and Modeling; Computational Biology/Bioinformatics; Physiological, Cellular and Medical Topics; Algorithms;
- 出版者：BioMed Central
- ISSN：1752-0509
- 卷排序：11
文摘
BackgroundGene regulatory networks with dynamics characterized by multiple stable states underlie cell fate-decisions. Quantitative models that can link molecular-level knowledge of gene regulation to a global understanding of network dynamics have the potential to guide cell-reprogramming strategies. Networks are often modeled by the stochastic Chemical Master Equation, but methods for systematic identification of key properties of the global dynamics are currently lacking.