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元建模工具箱MMTB:通过两个用例介绍的直观的基于网络的工具箱。

The Metano Modeling Toolbox MMTB: An Intuitive, Web-Based Toolbox Introduced by Two Use Cases.

作者信息

Koblitz Julia, Will Sabine Eva, Riemer S Alexander, Ulas Thomas, Neumann-Schaal Meina, Schomburg Dietmar

机构信息

Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Inhoffenstraße 7 B, 38124 Braunschweig, Germany.

Department of Bioinformatics and Biochemistry and Braunschweig Integrated Center of Systems Biology (BRICS), Technische Universität Braunschweig, Rebenring 56, 38106 Braunschweig, Germany.

出版信息

Metabolites. 2021 Feb 17;11(2):113. doi: 10.3390/metabo11020113.

Abstract

Genome-scale metabolic models are of high interest in a number of different research fields. Flux balance analysis (FBA) and other mathematical methods allow the prediction of the steady-state behavior of metabolic networks under different environmental conditions. However, many existing applications for flux optimizations do not provide a metabolite-centric view on fluxes. Metano is a standalone, open-source toolbox for the analysis and refinement of metabolic models. While flux distributions in metabolic networks are predominantly analyzed from a reaction-centric point of view, the Metano methods of split-ratio analysis and metabolite flux minimization also allow a metabolite-centric view on flux distributions. In addition, we present MMTB (Metano Modeling Toolbox), a web-based toolbox for metabolic modeling including a user-friendly interface to Metano methods. MMTB assists during bottom-up construction of metabolic models by integrating reaction and enzymatic annotation data from different databases. Furthermore, MMTB is especially designed for non-experienced users by providing an intuitive interface to the most commonly used modeling methods and offering novel visualizations. Additionally, MMTB allows users to upload their models, which can in turn be explored and analyzed by the community. We introduce MMTB by two use cases, involving a published model of and a newly created model of .

摘要

基因组规模的代谢模型在许多不同的研究领域备受关注。通量平衡分析(FBA)和其他数学方法能够预测代谢网络在不同环境条件下的稳态行为。然而,许多现有的通量优化应用并未提供以代谢物为中心的通量视角。Metano是一个用于代谢模型分析和优化的独立开源工具箱。虽然代谢网络中的通量分布主要是从以反应为中心的角度进行分析,但Metano的拆分比例分析和代谢物通量最小化方法也允许从以代谢物为中心的角度看待通量分布。此外,我们还展示了MMTB(Metano建模工具箱),这是一个基于网络的代谢建模工具箱,包括一个用户友好的Metano方法界面。MMTB通过整合来自不同数据库的反应和酶注释数据,在代谢模型的自下而上构建过程中提供协助。此外,MMTB专为非专业用户设计,提供了最常用建模方法的直观界面并提供新颖的可视化效果。此外,MMTB允许用户上传他们的模型,进而可供社区进行探索和分析。我们通过两个用例介绍MMTB,其中涉及一个已发表的[具体模型名称]模型和一个新创建的[具体模型名称]模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa50/7923039/87c4d5f54ba1/metabolites-11-00113-g001.jpg

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