For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
401
views
9
references
 Top references
cited by
384
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    7
    shares
      330
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      HMDB: the Human Metabolome Database

      research-article
      Author(s): 1 , 5 , 7 , * , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 5 , 5 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 , 2 , 3 , 3 , 3 , 3 , 6 , 6 , 6 , 6 , 4 , 3 , 1 , 3 , 4 , 2 , 6 , 1
      Publication date (Print):
      Journal: Nucleic Acids Research
      Publisher: Oxford University Press

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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:

          Related collections

          Most cited references9

          • Record: found
          • Abstract: found
          • Article: not found

          METLIN: a metabolite mass spectral database.

          Colin A Smith, Grace O'Maille, Elizabeth J. Want … (2005)
          Endogenous metabolites have gained increasing interest over the past 5 years largely for their implications in diagnostic and pharmaceutical biomarker discovery. METLIN (http://metlin.scripps.edu), a freely accessible web-based data repository, has been developed to assist in a broad array of metabolite research and to facilitate metabolite identification through mass analysis. METLINincludes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrometry (MS/MS) spectra, and LC/MS data.
          Article 0 comments Cited 515 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Database resources of the National Center for Biotechnology Information.

            David Wheeler, Tanya Barrett, Dennis A Benson … (2006)
            In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI's Web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups, Retroviral Genotyping Tools, HIV-1, Human Protein Interaction Database, SAGEmap, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool and the PubChem suite of small molecule databases. Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.
            Article 0 comments Cited 151 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Metabolomics: building on a century of biochemistry to guide human health.

              S. Watkins, J German, Bruce Hammock (2005)
              Medical diagnosis and treatment efficacy will improve significantly when a more personalized system for health assessment is implemented. This system will require diagnostics that provide sufficiently detailed information about the metabolic status of individuals such that assay results will be able to guide food, drug and lifestyle choices to maintain or improve distinct aspects of health without compromising others. Achieving this goal will use the new science of metabolomics - comprehensive metabolic profiling of individuals linked to the biological understanding of human integrative metabolism. Candidate technologies to accomplish this goal are largely available, yet they have not been brought into practice for this purpose. Metabolomic technologies must be sufficiently rapid, accurate and affordable to be routinely accessible to both healthy and acutely ill individuals. The use of metabolomic data to predict the health trajectories of individuals will require bioinformatic tools and quantitative reference databases. These databases containing metabolite profiles from the population must be built, stored and indexed according to metabolic and health status. Building and annotating these databases with the knowledge to predict how a specific metabolic pattern from an individual can be adjusted with diet, drugs and lifestyle to improve health represents a logical application of the biochemistry knowledge that the life sciences have produced over the past 100 years.
              Article 0 comments Cited 96 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (iso-abbrev): Nucleic Acids Res
                Journal ID (pmc): nar
                Journal ID (publisher-id): Nucleic Acids Research
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date (Print): January 2007
                Volume: 35
                Issue: Database issue
                Pages: D521-D526
                Affiliations
                1Department of Computing Science, , University of Alberta Edmonton, AB, Canada T6G 2E8
                2Department of Biochemistry, , University of Alberta Edmonton, AB, Canada T6G 2E8
                3Department of Chemistry, , University of Alberta Edmonton, AB, Canada T6G 2E8
                4Department of Medicine, , University of Alberta Edmonton, AB, Canada T6G 2E8
                5Department of Biological Sciences, University of Alberta Edmonton, AB, Canada T6G 2E8
                6Department of Biological Sciences, University of Calgary Calgary, AB, Canada T2N 1N4
                7National Institute for Nanotechnology, 11421 Saskatchewan Drive Edmonton, AB, Canada T6G 2M9
                Author notes
                *To whom correspondence should be addressed. Tel: +780 492 0383; Fax: +780 492 1071; Email: david.wishart@ 123456ualberta.ca
                Article
                DOI: 10.1093/nar/gkl923
                PMC ID: 1899095
                PubMed ID: 17202168
                SO-VID: bf9508aa-e5d4-4698-ab96-c199e370e95d
                Copyright © © 2006 The Author(s)
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 16 August 2006
                Date revision received : 15 October 2006
                Date accepted : 17 October 2006
                Categories
                Subject: Articles

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

                Comments

                Comment on this article

                scite_

                Similar content330

                See all similar

                Cited by901

                See all cited by

                Most referenced authors1,011

                See all reference authors