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Metabolites 2015, 5(2), 291-310; doi:10.3390/metabo5020291

Computational Metabolomics Operations at BioCyc.org

Bioinformatics Research Group, SRI International, 333 Ravenswood Ave AE206, Menlo Park, CA 94025, USA
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Academic Editor: Peter Meikle
Received: 20 November 2014 / Revised: 28 February 2015 / Accepted: 30 March 2015 / Published: 22 May 2015
(This article belongs to the Special Issue Bioinformatics and Data Analysis)
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Abstract

BioCyc.org is a genome and metabolic pathway web portal covering 5500 organisms, including Homo sapiens, Arabidopsis thaliana, Saccharomyces cerevisiae and Escherichia coli. These organism-specific databases have undergone variable degrees of curation. The EcoCyc (Escherichia coli Encyclopedia) database is the most highly curated; its contents have been derived from 27,000 publications. The MetaCyc (Metabolic Encyclopedia) database within BioCyc is a “universal” metabolic database that describes pathways, reactions, enzymes and metabolites from all domains of life. Metabolic pathways provide an organizing framework for analyzing metabolomics data, and the BioCyc website provides computational operations for metabolomics data that include metabolite search and translation of metabolite identifiers across multiple metabolite databases. The site allows researchers to store and manipulate metabolite lists using a facility called SmartTables, which supports metabolite enrichment analysis. That analysis operation identifies metabolite sets that are statistically over-represented for the substrates of specific metabolic pathways. BioCyc also enables visualization of metabolomics data on individual pathway diagrams and on the organism-specific metabolic map diagrams that are available for every BioCyc organism. Most of these operations are available both interactively and as programmatic web services. View Full-Text
Keywords: metabolic pathways; metabolomics data analysis; metabolic database metabolic pathways; metabolomics data analysis; metabolic database
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Karp, P.D.; Billington, R.; Holland, T.A.; Kothari, A.; Krummenacker, M.; Weaver, D.; Latendresse, M.; Paley, S. Computational Metabolomics Operations at BioCyc.org. Metabolites 2015, 5, 291-310.

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