JuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language

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• 作者：David M. Bassen ; Michael Vilkhovoy ; Mason Minot ; Jonathan T. Butcher…
• 关键词：Ensemble modeling ; Multiobjective optimization ; Julia
• 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：1117KB
• 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

BackgroundEnsemble modeling is a promising approach for obtaining robust predictions and coarse grained population behavior in deterministic mathematical models. Ensemble approaches address model uncertainty by using parameter or model families instead of single best-fit parameters or fixed model structures. Parameter ensembles can be selected based upon simulation error, along with other criteria such as diversity or steady-state performance. Simulations using parameter ensembles can estimate confidence intervals on model variables, and robustly constrain model predictions, despite having many poorly constrained parameters.