Open AccessMOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks
Author(s) -
James J. Kelley,
Shay Maor,
Min Kyung Kim,
Anatoliy Lane,
Desmond S. Lun
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx240
Subject(s) - visualization , computer science , documentation , software , mit license , software visualization , metabolic network , identification (biology) , software engineering , automation , data mining , software development , computational biology , programming language , component based software engineering , biology , engineering , mechanical engineering , botany
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).
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