文章基本信息

标题：DISCOPOLIS: an algorithm for uniform sampling of metabolic flux distributions via iterative sequences of linear programs
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作者：Philippe Bogaerts ; Marianne Rooman
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：26
页码：269-274
DOI：10.1016/j.ifacol.2019.12.269
语种：English
出版社：Elsevier
摘要：Mathematical models of metabolic networks are often underdetermined systems with more unknown fluxes than available equality constraints describing mass balances and external flux measurements. After reduction of the flux space based on the available equality constraints, the admissible reduced fluxes belong to a convex polytope defined by the intersection of half-planes representing the inequality constraints(e.g.,upper and lower bounds of the fluxes). Random uniform sampling of this polytope allows building marginal distributions for each flux and computing the mean solution representative of the mean metabolism exhibited by the studied organism. This contribution proposes a new algorithm based on DIscrete Sampling of COnvex POlytopes via Linear program Iterative Sequences (DISCOPOLIS), in which the linear programs are iteratively used to constrain the solutions inside the polytope, taking into account all the previously estimated fluxes. The solutions are weighted to ensure sampling uniformity.
关键词：KeywordsMetabolic networkMetabolic Flux AnalysisFlux Balance AnalysisFlux Variability AnalysisMost Accurate Fluxesuniform samplinghit-and-run methodsunderdetermined systemsconstrained-based modeling