On expert curation and scalability: UniProtKB/Swiss-Prot as a case study
Biological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily scientific research by offering distilled, summarized and computable knowledge extracted from the literature by expert curators. While knowledgebases play an increasingly important role in the scienti...
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Veröffentlicht in: | Bioinformatics (Oxford, England) England), 2017-11, Vol.33 (21), p.3454-3460 |
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creator | Poux, Sylvain Arighi, Cecilia N Magrane, Michele Bateman, Alex Wei, Chih-Hsuan Lu, Zhiyong Boutet, Emmanuel Bye-A-Jee, Hema Famiglietti, Maria Livia Roechert, Bernd UniProt Consortium, The |
description | Biological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily scientific research by offering distilled, summarized and computable knowledge extracted from the literature by expert curators. While knowledgebases play an increasingly important role in the scientific community, their ability to keep up with the growth of biomedical literature is under scrutiny. Using UniProtKB/Swiss-Prot as a case study, we address this concern via multiple literature triage approaches.
With the assistance of the PubTator text-mining tool, we tagged more than 10 000 articles to assess the ratio of papers relevant for curation. We first show that curators read and evaluate many more papers than they curate, and that measuring the number of curated publications is insufficient to provide a complete picture as demonstrated by the fact that 8000-10 000 papers are curated in UniProt each year while curators evaluate 50 000-70 000 papers per year. We show that 90% of the papers in PubMed are out of the scope of UniProt, that a maximum of 2-3% of the papers indexed in PubMed each year are relevant for UniProt curation, and that, despite appearances, expert curation in UniProt is scalable.
UniProt is freely available at http://www.uniprot.org/.
sylvain.poux@sib.swiss.
Supplementary data are available at Bioinformatics online. |
doi_str_mv | 10.1093/bioinformatics/btx439 |
format | Article |
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With the assistance of the PubTator text-mining tool, we tagged more than 10 000 articles to assess the ratio of papers relevant for curation. We first show that curators read and evaluate many more papers than they curate, and that measuring the number of curated publications is insufficient to provide a complete picture as demonstrated by the fact that 8000-10 000 papers are curated in UniProt each year while curators evaluate 50 000-70 000 papers per year. We show that 90% of the papers in PubMed are out of the scope of UniProt, that a maximum of 2-3% of the papers indexed in PubMed each year are relevant for UniProt curation, and that, despite appearances, expert curation in UniProt is scalable.
UniProt is freely available at http://www.uniprot.org/.
sylvain.poux@sib.swiss.
Supplementary data are available at Bioinformatics online.</description><identifier>ISSN: 1367-4803</identifier><identifier>ISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btx439</identifier><identifier>PMID: 29036270</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>amino acid sequences ; bioinformatics ; case studies ; computer software ; Data Curation - statistics & numerical data ; Data Mining ; Databases, Protein - statistics & numerical data ; Humans ; Knowledge Bases ; Original Papers ; proteins ; PubMed - statistics & numerical data ; Review Literature as Topic ; Statistics as Topic</subject><ispartof>Bioinformatics (Oxford, England), 2017-11, Vol.33 (21), p.3454-3460</ispartof><rights>The Author 2017. Published by Oxford University Press.</rights><rights>The Author 2017. Published by Oxford University Press. 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c444t-826aaccfe8024feb2905ee371e8671472b305bc543200b247b464725e9d776423</citedby><cites>FETCH-LOGICAL-c444t-826aaccfe8024feb2905ee371e8671472b305bc543200b247b464725e9d776423</cites><orcidid>0000-0001-7299-6685</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860168/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860168/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29036270$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Kelso, Janet</contributor><creatorcontrib>Poux, Sylvain</creatorcontrib><creatorcontrib>Arighi, Cecilia N</creatorcontrib><creatorcontrib>Magrane, Michele</creatorcontrib><creatorcontrib>Bateman, Alex</creatorcontrib><creatorcontrib>Wei, Chih-Hsuan</creatorcontrib><creatorcontrib>Lu, Zhiyong</creatorcontrib><creatorcontrib>Boutet, Emmanuel</creatorcontrib><creatorcontrib>Bye-A-Jee, Hema</creatorcontrib><creatorcontrib>Famiglietti, Maria Livia</creatorcontrib><creatorcontrib>Roechert, Bernd</creatorcontrib><creatorcontrib>UniProt Consortium, The</creatorcontrib><title>On expert curation and scalability: UniProtKB/Swiss-Prot as a case study</title><title>Bioinformatics (Oxford, England)</title><addtitle>Bioinformatics</addtitle><description>Biological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily scientific research by offering distilled, summarized and computable knowledge extracted from the literature by expert curators. While knowledgebases play an increasingly important role in the scientific community, their ability to keep up with the growth of biomedical literature is under scrutiny. Using UniProtKB/Swiss-Prot as a case study, we address this concern via multiple literature triage approaches.
With the assistance of the PubTator text-mining tool, we tagged more than 10 000 articles to assess the ratio of papers relevant for curation. We first show that curators read and evaluate many more papers than they curate, and that measuring the number of curated publications is insufficient to provide a complete picture as demonstrated by the fact that 8000-10 000 papers are curated in UniProt each year while curators evaluate 50 000-70 000 papers per year. We show that 90% of the papers in PubMed are out of the scope of UniProt, that a maximum of 2-3% of the papers indexed in PubMed each year are relevant for UniProt curation, and that, despite appearances, expert curation in UniProt is scalable.
UniProt is freely available at http://www.uniprot.org/.
sylvain.poux@sib.swiss.
Supplementary data are available at Bioinformatics online.</description><subject>amino acid sequences</subject><subject>bioinformatics</subject><subject>case studies</subject><subject>computer software</subject><subject>Data Curation - statistics & numerical data</subject><subject>Data Mining</subject><subject>Databases, Protein - statistics & numerical data</subject><subject>Humans</subject><subject>Knowledge Bases</subject><subject>Original Papers</subject><subject>proteins</subject><subject>PubMed - statistics & numerical data</subject><subject>Review Literature as Topic</subject><subject>Statistics as Topic</subject><issn>1367-4803</issn><issn>1460-2059</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUclKBDEUDKK4f4KSo5d2Xtbu9iDo4IaCgnoOSSatkZ7OmKTV-XtbRgc9eXpbVVGPQmiPwCGBmo2MD75rQpzq7G0amfzBWb2CNgmTZcErQlaXPbANtJXSCwAIEHIdbdAamKQlbKLL2w67j5mLGds-Dlqhw7qb4GR1q41vfZ4f4cfO38WQr09H9-8-peJrwDphja1ODqfcT-Y7aK3RbXK733UbPZ6fPYwvi5vbi6vxyU1hOee5qKjU2trGVUB548zgRDjHSuIqWRJeUsNAGCs4owCG8tJwOWyFqydlKTll2-h4oTvrzdRNrOty1K2aRT_Vca6C9urvpfPP6im8KVFJILIaBA6-BWJ47V3KauqTdW2rOxf6pCgVjEqoCf8XSmpBCZCKkwEqFlAbQ0rRNUtHBNRXYOpvYGoR2MDb__3OkvWTEPsEy-GW8g</recordid><startdate>20171101</startdate><enddate>20171101</enddate><creator>Poux, Sylvain</creator><creator>Arighi, Cecilia N</creator><creator>Magrane, Michele</creator><creator>Bateman, Alex</creator><creator>Wei, Chih-Hsuan</creator><creator>Lu, Zhiyong</creator><creator>Boutet, Emmanuel</creator><creator>Bye-A-Jee, Hema</creator><creator>Famiglietti, Maria Livia</creator><creator>Roechert, Bernd</creator><creator>UniProt Consortium, The</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>7S9</scope><scope>L.6</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-7299-6685</orcidid></search><sort><creationdate>20171101</creationdate><title>On expert curation and scalability: UniProtKB/Swiss-Prot as a case study</title><author>Poux, Sylvain ; Arighi, Cecilia N ; Magrane, Michele ; Bateman, Alex ; Wei, Chih-Hsuan ; Lu, Zhiyong ; Boutet, Emmanuel ; Bye-A-Jee, Hema ; Famiglietti, Maria Livia ; Roechert, Bernd ; UniProt Consortium, The</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c444t-826aaccfe8024feb2905ee371e8671472b305bc543200b247b464725e9d776423</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>amino acid sequences</topic><topic>bioinformatics</topic><topic>case studies</topic><topic>computer software</topic><topic>Data Curation - statistics & numerical data</topic><topic>Data Mining</topic><topic>Databases, Protein - statistics & numerical data</topic><topic>Humans</topic><topic>Knowledge Bases</topic><topic>Original Papers</topic><topic>proteins</topic><topic>PubMed - statistics & numerical data</topic><topic>Review Literature as Topic</topic><topic>Statistics as Topic</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Poux, Sylvain</creatorcontrib><creatorcontrib>Arighi, Cecilia N</creatorcontrib><creatorcontrib>Magrane, Michele</creatorcontrib><creatorcontrib>Bateman, Alex</creatorcontrib><creatorcontrib>Wei, Chih-Hsuan</creatorcontrib><creatorcontrib>Lu, Zhiyong</creatorcontrib><creatorcontrib>Boutet, Emmanuel</creatorcontrib><creatorcontrib>Bye-A-Jee, Hema</creatorcontrib><creatorcontrib>Famiglietti, Maria Livia</creatorcontrib><creatorcontrib>Roechert, Bernd</creatorcontrib><creatorcontrib>UniProt Consortium, The</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>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Bioinformatics (Oxford, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Poux, Sylvain</au><au>Arighi, Cecilia N</au><au>Magrane, Michele</au><au>Bateman, Alex</au><au>Wei, Chih-Hsuan</au><au>Lu, Zhiyong</au><au>Boutet, Emmanuel</au><au>Bye-A-Jee, Hema</au><au>Famiglietti, Maria Livia</au><au>Roechert, Bernd</au><au>UniProt Consortium, The</au><au>Kelso, Janet</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On expert curation and scalability: UniProtKB/Swiss-Prot as a case study</atitle><jtitle>Bioinformatics (Oxford, England)</jtitle><addtitle>Bioinformatics</addtitle><date>2017-11-01</date><risdate>2017</risdate><volume>33</volume><issue>21</issue><spage>3454</spage><epage>3460</epage><pages>3454-3460</pages><issn>1367-4803</issn><issn>1460-2059</issn><eissn>1367-4811</eissn><abstract>Biological knowledgebases, such as UniProtKB/Swiss-Prot, constitute an essential component of daily scientific research by offering distilled, summarized and computable knowledge extracted from the literature by expert curators. While knowledgebases play an increasingly important role in the scientific community, their ability to keep up with the growth of biomedical literature is under scrutiny. Using UniProtKB/Swiss-Prot as a case study, we address this concern via multiple literature triage approaches.
With the assistance of the PubTator text-mining tool, we tagged more than 10 000 articles to assess the ratio of papers relevant for curation. We first show that curators read and evaluate many more papers than they curate, and that measuring the number of curated publications is insufficient to provide a complete picture as demonstrated by the fact that 8000-10 000 papers are curated in UniProt each year while curators evaluate 50 000-70 000 papers per year. We show that 90% of the papers in PubMed are out of the scope of UniProt, that a maximum of 2-3% of the papers indexed in PubMed each year are relevant for UniProt curation, and that, despite appearances, expert curation in UniProt is scalable.
UniProt is freely available at http://www.uniprot.org/.
sylvain.poux@sib.swiss.
Supplementary data are available at Bioinformatics online.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>29036270</pmid><doi>10.1093/bioinformatics/btx439</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-7299-6685</orcidid><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; Oxford Journals Open Access Collection; EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection |
subjects | amino acid sequences bioinformatics case studies computer software Data Curation - statistics & numerical data Data Mining Databases, Protein - statistics & numerical data Humans Knowledge Bases Original Papers proteins PubMed - statistics & numerical data Review Literature as Topic Statistics as Topic |
title | On expert curation and scalability: UniProtKB/Swiss-Prot as a case study |
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