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

James J. Kelley, Shay Maor, Min Kyung Kim, Anatoliy Lane, Desmond S. Lun

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)2596-2597
Number of pages2
JournalBioinformatics (Oxford, England)
Volume33
Issue number16
DOIs
StatePublished - Aug 15 2017

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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