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FluxML的设计:一种用于C代谢通量分析的通用建模语言。

The Design of FluxML: A Universal Modeling Language for C Metabolic Flux Analysis.

作者信息

Beyß Martin, Azzouzi Salah, Weitzel Michael, Wiechert Wolfgang, Nöh Katharina

机构信息

Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany.

Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University, Aachen, Germany.

出版信息

Front Microbiol. 2019 May 24;10:1022. doi: 10.3389/fmicb.2019.01022. eCollection 2019.

Abstract

C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. C MFA, however, stands out from other "-omics sciences," in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an "all-around carefree package" for C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of C MFA.

摘要

13C代谢通量分析(MFA)是一种首选方法,用于在代谢准稳态条件下详细推断活生物体中的细胞内代谢通量。该技术自二十年来不断发展,为生物技术和健康相关研究的各个领域中生物体的定量表征做出了重大贡献。然而,13C MFA与其他“组学科学”不同,因为它不仅需要实验分析数据,还需要数学模型和计算工具集来推断感兴趣的量,即代谢通量。目前,这些模型无法在不同实验室之间方便地交换。在此,我们提出了用于指定13C MFA模型的与实现无关的模型描述语言FluxML。FluxML的核心捕获了代谢反应网络以及原子映射、对模型参数的约束和大量数据配置。特别是,我们描述了塑造FluxML语言的主导设计过程。我们展示了FluxML在表示13C MFA领域中许多当代实验分析要求方面的实用性。FluxML的主要目标是提供一种合理、开放且面向未来的语言,以明确表达和保存模型重用、交换和比较所需的所有必要信息。除了FluxML,还提供了几个强大的计算工具,便于处理,同时保持最大的灵活性。总之,FluxML集合是13C MFA建模人员的“全方位无忧包”。我们相信,FluxML提高了科学生产力以及透明度,从而有助于13C MFA领域计算建模工作的效率和可重复性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d078/6543931/669b1693ffe2/fmicb-10-01022-g0001.jpg

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