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HMDB: The human metabolome database

TLDR
The Human Metabolome Database is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community.
Abstract
The Human Metabolome Database (HMDB) is currently the most complete and comprehensive curated collection of human metabolite and human metabolism data in the world. It contains records for more than 2180 endogenous metabolites with information gathered from thousands of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the HMDB also contains an extensive collection of experimental metabolite concentration data compiled from hundreds of mass spectra (MS) and Nuclear Magnetic resonance (NMR) metabolomic analyses performed on urine, blood and cerebrospinal fluid samples. This is further supplemented with thousands of NMR and MS spectra collected on purified, reference metabolites. Each metabolite entry in the HMDB contains an average of 90 separate data fields including a comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, biofluid concentrations, disease associations, pathway information, enzyme data, gene sequence data, SNP and mutation data as well as extensive links to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided. The HMDB is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. The HMDB is available at: www.hmdb.ca

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References
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Journal ArticleDOI

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

TL;DR: A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original.
Journal ArticleDOI

Database resources of the National Center for Biotechnology Information

TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
Journal ArticleDOI

SMILES, a chemical language and information system. 1. introduction to methodology and encoding rules

TL;DR: This chapter discusses the construction of Benzenoid and Coronoid Hydrocarbons through the stages of enumeration, classification, and topological properties in a number of computers used for this purpose.
Journal ArticleDOI

The KEGG resource for deciphering the genome

TL;DR: A knowledge-based approach for network prediction is developed, which is to predict, given a complete set of genes in the genome, the protein interaction networks that are responsible for various cellular processes.
Journal ArticleDOI

The Universal Protein Resource (UniProt)

TL;DR: During 2004, tens of thousands of Knowledgebase records got manually annotated or updated; the UniProt keyword list got augmented by additional keywords; the documentation of the keywords and are continuously overhauling and standardizing the annotation of post-translational modifications.
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