Jensen Paul A
Department of Bioengineering and Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
Methods Mol Biol. 2018;1716:337-351. doi: 10.1007/978-1-4939-7528-0_15.
Genome-scale models have expanded beyond their metabolic origins. Multiple modeling frameworks are required to combine metabolism with enzymatic networks, transcription, translation, and regulation. Mathematical programming offers a powerful set of tools for tackling these "multi-modality" models, although special attention must be paid to the connections between modeling types. This chapter reviews common methods for combining metabolic and discrete logical models into a single mathematical programming framework. Best practices, caveats, and recommendations are presented for the most commonly used software packages. Methods for troubleshooting large sets of logical rules are also discussed.
基因组尺度模型已超越其代谢起源。需要多个建模框架来将代谢与酶网络、转录、翻译及调控相结合。数学规划提供了一套强大的工具来处理这些“多模态”模型,不过必须特别关注建模类型之间的联系。本章回顾了将代谢模型与离散逻辑模型组合成单一数学规划框架的常用方法。针对最常用的软件包,介绍了最佳实践、注意事项及建议。还讨论了处理大量逻辑规则的故障排除方法。