GEM System: Automatic Prototyping of Cell-wide Metabolic Pathway Models from Genomes

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2006 Mar 24

PMID 16553966

Citations 17

Authors

Kazuharu Arakawa

Yohei Yamada

Kosaku Shinoda

Yoichi Nakayama

Masaru Tomita

Affiliations

Soon will be listed here.

Abstract

Background: Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology.

Results: We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model.

Conclusion: The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

Citing Articles

Technologies for whole-cell modeling: Genome-wide reconstruction of a cell in silico.

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Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges.

Bi X, Liu Y, Li J, Du G, Lv X, Liu L Biomolecules. 2022; 12(5).

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Metabolic Modelling as a Framework for Metabolomics Data Integration and Analysis.

Volkova S, Matos M, Mattanovich M, Marin de Mas I Metabolites. 2020; 10(8).

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A systematic assessment of current genome-scale metabolic reconstruction tools.

Mendoza S, Olivier B, Molenaar D, Teusink B Genome Biol. 2019; 20(1):158.

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Fast automated reconstruction of genome-scale metabolic models for microbial species and communities.

Machado D, Andrejev S, Tramontano M, Patil K Nucleic Acids Res. 2018; 46(15):7542-7553.

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