MetaMapR: pathway independent metabolomic network analysis incorporating unknowns
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 exper...
Gespeichert in:
| Veröffentlicht in: | Bioinformatics 2015-08, Vol.31 (16), p.2757-2760 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2760 |
|---|---|
| container_issue | 16 |
| container_start_page | 2757 |
| container_title | Bioinformatics |
| container_volume | 31 |
| creator | Grapov, Dmitry Wanichthanarak, Kwanjeera Fiehn, Oliver |
| description | 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 >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.
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/.
ofiehn@ucdavis.edu. |
| doi_str_mv | 10.1093/bioinformatics/btv194 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4528626</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1709168634</sourcerecordid><originalsourceid>FETCH-LOGICAL-c543t-a2a6206d21b3e35e875d55dc288562134119d97505d6db699300063b22c2faab3</originalsourceid><addsrcrecordid>eNqNkV1PwjAUhhujEUV_gmaX3kz6sXabFyaG-JVAjEavm64rUNna2W4Q_r0lIJE7bnranPe8fU5eAK4QvEUwJ4NCW20m1tWi1dIPinaB8uQInCHC0jjJEDre3SHpgXPvvyGEFFJ2CnqYZkkaXmfgfaxaMRbNx13UiHa2FKtIm1I1KhymjerQLWxlay0jo9qldfNIGFGtvPZBKK1rrAsEZhp1Zm7s0vgLcDIRlVeX29oHX0-Pn8OXePT2_Dp8GMWSJqSNBRYMQ1ZiVBBFqMpSWlJaSpxllGFEEoTyMk8DcMnKguU5CfiMFBhLPBGiIH1wv_FtuqJWpQy4TlS8cboWbsWt0Hy_Y_SMT-2CJxRnDLNgcLM1cPanU77ltfZSVZUwynaeozR8mTCC8wOkMEcsYyQ5RIoZpSRdu9KNVDrrvVOTHTyCfB0y3w-Zb0IOc9f_N99N_aVKfgHYFqnz</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1702655379</pqid></control><display><type>article</type><title>MetaMapR: pathway independent metabolomic network analysis incorporating unknowns</title><source>MEDLINE</source><source>Oxford Journals Open Access Collection</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Grapov, Dmitry ; Wanichthanarak, Kwanjeera ; Fiehn, Oliver</creator><creatorcontrib>Grapov, Dmitry ; Wanichthanarak, Kwanjeera ; Fiehn, Oliver</creatorcontrib><description>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 >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.
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/.
ofiehn@ucdavis.edu.</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1367-4811</identifier><identifier>EISSN: 1460-2059</identifier><identifier>DOI: 10.1093/bioinformatics/btv194</identifier><identifier>PMID: 25847005</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Applications Notes ; Biochemistry ; Metabolic Networks and Pathways ; Metabolites ; Metabolomics - methods ; Network analysis ; Networks ; Pathways ; Similarity ; Software ; Visualization ; Web Browser</subject><ispartof>Bioinformatics, 2015-08, Vol.31 (16), p.2757-2760</ispartof><rights>The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.</rights><rights>The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c543t-a2a6206d21b3e35e875d55dc288562134119d97505d6db699300063b22c2faab3</citedby><cites>FETCH-LOGICAL-c543t-a2a6206d21b3e35e875d55dc288562134119d97505d6db699300063b22c2faab3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4528626/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4528626/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25847005$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Grapov, Dmitry</creatorcontrib><creatorcontrib>Wanichthanarak, Kwanjeera</creatorcontrib><creatorcontrib>Fiehn, Oliver</creatorcontrib><title>MetaMapR: pathway independent metabolomic network analysis incorporating unknowns</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>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 >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.
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/.
ofiehn@ucdavis.edu.</description><subject>Applications Notes</subject><subject>Biochemistry</subject><subject>Metabolic Networks and Pathways</subject><subject>Metabolites</subject><subject>Metabolomics - methods</subject><subject>Network analysis</subject><subject>Networks</subject><subject>Pathways</subject><subject>Similarity</subject><subject>Software</subject><subject>Visualization</subject><subject>Web Browser</subject><issn>1367-4803</issn><issn>1367-4811</issn><issn>1460-2059</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkV1PwjAUhhujEUV_gmaX3kz6sXabFyaG-JVAjEavm64rUNna2W4Q_r0lIJE7bnranPe8fU5eAK4QvEUwJ4NCW20m1tWi1dIPinaB8uQInCHC0jjJEDre3SHpgXPvvyGEFFJ2CnqYZkkaXmfgfaxaMRbNx13UiHa2FKtIm1I1KhymjerQLWxlay0jo9qldfNIGFGtvPZBKK1rrAsEZhp1Zm7s0vgLcDIRlVeX29oHX0-Pn8OXePT2_Dp8GMWSJqSNBRYMQ1ZiVBBFqMpSWlJaSpxllGFEEoTyMk8DcMnKguU5CfiMFBhLPBGiIH1wv_FtuqJWpQy4TlS8cboWbsWt0Hy_Y_SMT-2CJxRnDLNgcLM1cPanU77ltfZSVZUwynaeozR8mTCC8wOkMEcsYyQ5RIoZpSRdu9KNVDrrvVOTHTyCfB0y3w-Zb0IOc9f_N99N_aVKfgHYFqnz</recordid><startdate>20150815</startdate><enddate>20150815</enddate><creator>Grapov, Dmitry</creator><creator>Wanichthanarak, Kwanjeera</creator><creator>Fiehn, Oliver</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QO</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7SC</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>5PM</scope></search><sort><creationdate>20150815</creationdate><title>MetaMapR: pathway independent metabolomic network analysis incorporating unknowns</title><author>Grapov, Dmitry ; Wanichthanarak, Kwanjeera ; Fiehn, Oliver</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c543t-a2a6206d21b3e35e875d55dc288562134119d97505d6db699300063b22c2faab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Applications Notes</topic><topic>Biochemistry</topic><topic>Metabolic Networks and Pathways</topic><topic>Metabolites</topic><topic>Metabolomics - methods</topic><topic>Network analysis</topic><topic>Networks</topic><topic>Pathways</topic><topic>Similarity</topic><topic>Software</topic><topic>Visualization</topic><topic>Web Browser</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Grapov, Dmitry</creatorcontrib><creatorcontrib>Wanichthanarak, Kwanjeera</creatorcontrib><creatorcontrib>Fiehn, Oliver</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Grapov, Dmitry</au><au>Wanichthanarak, Kwanjeera</au><au>Fiehn, Oliver</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MetaMapR: pathway independent metabolomic network analysis incorporating unknowns</atitle><jtitle>Bioinformatics</jtitle><addtitle>Bioinformatics</addtitle><date>2015-08-15</date><risdate>2015</risdate><volume>31</volume><issue>16</issue><spage>2757</spage><epage>2760</epage><pages>2757-2760</pages><issn>1367-4803</issn><eissn>1367-4811</eissn><eissn>1460-2059</eissn><abstract>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 >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.
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/.
ofiehn@ucdavis.edu.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>25847005</pmid><doi>10.1093/bioinformatics/btv194</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1367-4803 |
| ispartof | Bioinformatics, 2015-08, Vol.31 (16), p.2757-2760 |
| issn | 1367-4803 1367-4811 1460-2059 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4528626 |
| source | MEDLINE; Oxford Journals Open Access Collection; EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection |
| subjects | Applications Notes Biochemistry Metabolic Networks and Pathways Metabolites Metabolomics - methods Network analysis Networks Pathways Similarity Software Visualization Web Browser |
| title | MetaMapR: pathway independent metabolomic network analysis incorporating unknowns |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T07%3A39%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=MetaMapR:%20pathway%20independent%20metabolomic%20network%20analysis%20incorporating%20unknowns&rft.jtitle=Bioinformatics&rft.au=Grapov,%20Dmitry&rft.date=2015-08-15&rft.volume=31&rft.issue=16&rft.spage=2757&rft.epage=2760&rft.pages=2757-2760&rft.issn=1367-4803&rft.eissn=1367-4811&rft_id=info:doi/10.1093/bioinformatics/btv194&rft_dat=%3Cproquest_pubme%3E1709168634%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1702655379&rft_id=info:pmid/25847005&rfr_iscdi=true |