國家衛生研究院 NHRI:Item 3990099045/6408
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    题名: GEMSiRV: A software platform for GEnome-scale metabolic model simulation, reconstruction and visualization
    作者: Liao, YC;Tsai, MH;Chen, FC;Hsiung, CA
    贡献者: Division of Biostatistics and Bioinformatics
    摘要: MOTIVATION: Genome-scale metabolic network models have become an indispensable part of the increasingly important field of systems biology. Metabolic systems biology studies usually include three major components - network model construction, objective- and experiment-guided model editing and visualization, and simulation studies based mainly on flux balance analyses. Bioinformatics tools are required to facilitate these complicated analyses. Although some of the required functions have been served separately by existing tools, a free software resource that simultaneously serves the needs of the three major components is not yet available. RESULTS: Here we present a software platform, GEMSiRV, to provide functionalities of easy metabolic network drafting and editing, amenable network visualization for experimental data integration, and flux balance analysis tools for simulation studies. GEMSiRV comes with downloadable, ready-to-use public-domain metabolic models, reference metabolite/reaction databases, and metabolic network maps, all of which can be input into GEMSiRV as the starting materials for network construction or simulation analyses. Furthermore, all of the GEMSiRV-generated metabolic models and analysis results, including projects in progress, can be easily exchanged in the research community. GEMSiRV is a powerful integrative resource that may facilitate the development of systems biology studies.
    日期: 2012-07
    關聯: Bioinformatics. 2012 Jul;28(13):1752-1758.
    Link to: http://dx.doi.org/10.1093/bioinformatics/bts267
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1367-4803&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000305825600012
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84864000794
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