Literature DB >> 28430868

MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

James J Kelley1, Shay Maor1, Min Kyung Kim1, Anatoliy Lane1, Desmond S Lun1,2.   

Abstract

SUMMARY: Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii).
AVAILABILITY AND IMPLEMENTATION: MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. CONTACT: dslun@rutgers.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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Year:  2017        PMID: 28430868     DOI: 10.1093/bioinformatics/btx240

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  1 in total

Review 1.  Integrating bioinformatics approaches for a comprehensive interpretation of metabolomics datasets.

Authors:  Dinesh Kumar Barupal; Sili Fan; Oliver Fiehn
Journal:  Curr Opin Biotechnol       Date:  2018-02-06       Impact factor: 9.740

  1 in total

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