Gsmodutils: A python based framework for test-driven genome scale metabolic model development
Gsmodutils: A python based framework for test-driven genome scale metabolic model development
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Gsmodutils：基于 Python 的框架，用于测试驱动的基因组规模代谢模型开发
DOI：
10.1101/430116
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Gilbert J
中科院分区：
文献类型：
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作者：
Gilbert J
基因组尺度代谢模型（GSMMs）对于系统生物学和代谢工程研究越来越重要，因为它们能够模拟复杂的稳态行为。这种形式的基于约束的模型可以包括数千种反应和代谢物，其中许多关键途径只有在特定的模拟设置中才会被激活。然而，尽管它们的广泛使用，权力和工具的可用性，以帮助建设和分析大规模的模型，很少的方法，建议他们继续管理。例如，当基因组注释更新或发现关于行为的新理解时，通常需要改变模型以反映这一点。这是迅速成为一个问题，工业系统和合成生物技术的应用，这需要高质量的可重复使用的模型不可或缺的设计，构建，测试和学习cycle.ResultsAs的一部分，正在进行的努力，以提高基因组规模的代谢分析，我们已经开发出一个测试驱动的开发方法，从不同来源的验证数据的持续集成。为基于COBRApy的开源技术做出贡献，我们开发了gmodutilmodelling框架，强调通过定义的测试用例进行测试驱动的模型设计。至关重要的是，不同的条件是可配置的，允许用户检查不同的设计或策展如何影响广泛的系统behaviors.Availability和implementationThe软件框架中描述的模型版本之间的错误最小化。本文是开源的，并免费从http://github.com/SBRCNottingham/gsmodutils.Supplementary信息补充数据可在Bioinformaticsonline。
MotivationGenome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-state behaviour. Constraints based models of this form can include thousands of reactions and metabolites, with many crucial pathways that only become activated in specific simulation settings. However, despite their widespread use, power and the availability of tools to aid with the construction and analysis of large scale models, little methodology is suggested for their continued management. For example, when genome annotations are updated or new understanding regarding behaviour is discovered, models often need to be altered to reflect this. This is quickly becoming an issue for industrial systems and synthetic biotechnology applications, which require good quality reusable models integral to the design, build, test and learn cycle.ResultsAs part of an ongoing effort to improve genome scale metabolic analysis, we have developed a test-driven development methodology for the continuous integration of validation data from different sources. Contributing to the open source technology based around COBRApy, we have developed thegsmodutilsmodelling framework placing an emphasis on test-driven design of models through defined test cases. Crucially, different conditions are configurable allowing users to examine how different designs or curation impact a wide range of system behaviours, minimizing error between model versions.Availability and implementationThe software framework described within this paper is open source and freely available from http://github.com/SBRCNottingham/gsmodutils.Supplementary informationSupplementary data are available atBioinformaticsonline.