文章基本信息

标题：Challenges in the calibration of large-scale ordinary differential equation models
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作者：Eva-Maria Kapfer ; Paul Stapor ; Jan Hasenauer 等
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：58-64
DOI：10.1016/j.ifacol.2019.12.236
语种：English
出版社：Elsevier
摘要：Mathematical models based on ordinary differential equations have been employed with great success to study complex biological systems. With soaring data availability, more and more models of increasing size are being developed. When working with these large-scale models, several challenges arise, such as high computation times or poor identifiability of model parameters. In this work, we review and illustrate the most common challenges using a published model of cellular metabolism. We summarize currently available methods to deal with some of these challenges while focusing on reproducibility and reusability of models, efficient and robust model simulation and parameter estimation.
关键词：KeywordsDifferential equationsDynamic modellingSteady statesLarge-scale systemsParameter estimationReproducibility