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

Phaeobacter inhibens flux balance analysis metabolic modeling systems biology tropodithietic acid

Journal

Metabolites
ISSN: 2218-1989
Titre abrégé: Metabolites
Pays: Switzerland
ID NLM: 101578790

Informations de publication

Date de publication:
17 Feb 2021
Historique:
received: 20 01 2021
revised: 12 02 2021
accepted: 15 02 2021
entrez: 6 3 2021
pubmed: 7 3 2021
medline: 7 3 2021
Statut: epublish

Résumé

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

Identifiants

pubmed: 33671140
pii: metabo11020113
doi: 10.3390/metabo11020113
pmc: PMC7923039
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Deutsche Forschungsgemeinschaft
ID : SFB TRR 51
Organisme : Bundesministerium für Bildung und Forschung
ID : 031L0078E
Organisme : Sixth Framework Programme
ID : LSHG-CT-2005-518254

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Auteurs

Julia Koblitz (J)

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.

Sabine Eva Will (SE)

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.

S Alexander Riemer (SA)

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

Thomas Ulas (T)

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

Meina Neumann-Schaal (M)

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.

Dietmar Schomburg (D)

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

Classifications MeSH