Metab2MeSH: annotating compounds with medical subject headings
Author(s) -
Maureen A. Sartor,
Alex Ade,
Zach Wright,
David States,
Gilbert S. Omenn,
Brian D. Athey,
Alla Karnovsky
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts156
Subject(s) - pubchem , controlled vocabulary , computer science , subject (documents) , variety (cybernetics) , task (project management) , metabolome , vocabulary , data science , world wide web , information retrieval , computational biology , bioinformatics , metabolomics , biology , artificial intelligence , linguistics , philosophy , management , economics
Progress in high-throughput genomic technologies has led to the development of a variety of resources that link genes to functional information contained in the biomedical literature. However, tools attempting to link small molecules to normal and diseased physiology and published data relevant to biologists and clinical investigators, are still lacking. With metabolomics rapidly emerging as a new omics field, the task of annotating small molecule metabolites becomes highly relevant. Our tool Metab2MeSH uses a statistical approach to reliably and automatically annotate compounds with concepts defined in Medical Subject Headings, and the National Library of Medicine's controlled vocabulary for biomedical concepts. These annotations provide links from compounds to biomedical literature and complement existing resources such as PubChem and the Human Metabolome Database.
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