{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T09:18:52Z","timestamp":1772011132384,"version":"3.50.1"},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,8,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Metabolic network mapping is a widely used approach for integration of metabolomic experimental results with biological domain knowledge. However, current approaches can be limited by biochemical domain or pathway knowledge which results in sparse disconnected graphs for real world metabolomic experiments. MetaMapR integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown. Network calculation is enhanced through an interface to the Chemical Translation System, which allows metabolite identifier translation between &amp;gt;200 common biochemical databases. Analysis results are presented as interactive visualizations or can be exported as high-quality graphics and numerical tables which can be imported into common network analysis and visualization tools.<\/jats:p>\n               <jats:p>Availability and Implementation: Freely available at http:\/\/dgrapov.github.io\/MetaMapR\/. Requires R and a modern web browser. Installation instructions, tutorials and application examples are available at http:\/\/dgrapov.github.io\/MetaMapR\/.<\/jats:p>\n               <jats:p>Contact: \u00a0ofiehn@ucdavis.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv194","type":"journal-article","created":{"date-parts":[[2015,4,7]],"date-time":"2015-04-07T00:02:55Z","timestamp":1428364975000},"page":"2757-2760","source":"Crossref","is-referenced-by-count":104,"title":["MetaMapR: pathway independent metabolomic network analysis incorporating unknowns"],"prefix":"10.1093","volume":"31","author":[{"given":"Dmitry","family":"Grapov","sequence":"first","affiliation":[{"name":"1 National Institutes of Health West Coast Metabolomics Center,"},{"name":"2 Genome Center, University of California Davis, Davis CA 95616, USA and"}]},{"given":"Kwanjeera","family":"Wanichthanarak","sequence":"additional","affiliation":[{"name":"1 National Institutes of Health West Coast Metabolomics Center,"},{"name":"2 Genome Center, University of California Davis, Davis CA 95616, USA and"}]},{"given":"Oliver","family":"Fiehn","sequence":"additional","affiliation":[{"name":"1 National Institutes of Health West Coast Metabolomics Center,"},{"name":"2 Genome Center, University of California Davis, Davis CA 95616, USA and"},{"name":"3 King Abdulaziz University, Biochemistry Department, Jeddah, Saudi Arabia"}]}],"member":"286","published-online":{"date-parts":[[2015,4,5]]},"reference":[{"key":"2023020202200478400_btv194-B1","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1186\/1471-2105-13-99","article-title":"MetaMapp: mapping and visualizing metabolomic data by integrating information from biochemical pathways and chemical and mass spectral similarity","volume":"13","author":"Barupal","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2023020202200478400_btv194-B2","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1007\/11530084_18","article-title":"Setup and annotation of metabolomic experiments by integrating biological and mass spectrometric metadata","volume-title":"Data Integration in the Life Sciences","author":"Fiehn","year":"2005"},{"key":"2023020202200478400_btv194-B3","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1093\/bioinformatics\/btq048","article-title":"Metscape: a Cytoscape plug-in for visualizing and interpreting metabolomic data in the context of human metabolic networks","volume":"26","author":"Gao","year":"2010","journal-title":"Bioinformatics"},{"key":"2023020202200478400_btv194-B4","doi-asserted-by":"crossref","first-page":"e48852","DOI":"10.1371\/journal.pone.0048852","article-title":"Type 2 diabetes associated changes in the plasma non-esterified fatty acids, oxylipins and endocannabinoids","volume":"7","author":"Grapov","year":"2012","journal-title":"PloS one"},{"key":"2023020202200478400_btv194-B5","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s11306-014-0706-2","article-title":"Diabetes associated metabolomic perturbations in NOD mice","volume":"11","author":"Grapov","year":"2014","journal-title":"Metabolomics"},{"key":"2023020202200478400_btv194-B6","doi-asserted-by":"crossref","first-page":"D199","DOI":"10.1093\/nar\/gkt1076","article-title":"Data, information, knowledge and principle: back to metabolism in KEGG","volume":"42","author":"Kanehisa","year":"2014","journal-title":"Nucleic Acids Res."},{"key":"2023020202200478400_btv194-B7","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1093\/bioinformatics\/btr661","article-title":"Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data","volume":"28","author":"Karnovsky","year":"2012","journal-title":"Bioinformatics"},{"key":"2023020202200478400_btv194-B8","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/s12020-012-9760-6","article-title":"1,5-Anhydroglucitol in diabetes mellitus","volume":"43","author":"Kim","year":"2013","journal-title":"Endocrine"},{"key":"2023020202200478400_btv194-B9","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1186\/1471-2105-9-559","article-title":"WGCNA: an R package for weighted correlation network analysis","volume":"9","author":"Langfelder","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2023020202200478400_btv194-B10","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: a software environment for integrated models of biomolecular interaction networks","volume":"13","author":"Shannon","year":"2003","journal-title":"Genome Res."},{"key":"2023020202200478400_btv194-B11","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1016\/1044-0305(94)87009-8","article-title":"Optimization and testing of mass spectral library search algorithms for compound identification","volume":"5","author":"Stein","year":"1994","journal-title":"J. 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