{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T14:51:43Z","timestamp":1789051903042,"version":"build-2803163510"},"reference-count":12,"publisher":"Oxford University Press (OUP)","issue":"19","license":[{"start":{"date-parts":[[2016,10,26]],"date-time":"2016-10-26T00:00:00Z","timestamp":1477440000000},"content-version":"vor","delay-in-days":138,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Summary: Medical Subject Headings (MeSH\u00ae) is a controlled vocabulary for indexing and searching biomedical literature. MeSH terms and subheadings are organized in a hierarchical structure and are used to indicate the topics of an article. Biologists can use either MeSH terms as queries or the MeSH interface provided in PubMed\u00ae for searching PubMed abstracts. However, these are rarely used, and there is no convenient way to link standardized MeSH terms to user queries. Here, we introduce a web interface which allows users to enter queries to find MeSH terms closely related to the queries. Our method relies on co-occurrence of text words and MeSH terms to find keywords that are related to each MeSH term. A query is then matched with the keywords for MeSH terms, and candidate MeSH terms are ranked based on their relatedness to the query. The experimental results show that our method achieves the best performance among several term extraction approaches in terms of topic coherence. Moreover, the interface can be effectively used to find full names of abbreviations and to disambiguate user queries.<\/jats:p>\n                  <jats:p>Availability and Implementation: \u00a0https:\/\/www.ncbi.nlm.nih.gov\/IRET\/MESHABLE\/<\/jats:p>\n                  <jats:p>Contact: \u00a0sun.kim@nih.gov<\/jats:p>\n                  <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw331","type":"journal-article","created":{"date-parts":[[2016,6,10]],"date-time":"2016-06-10T23:54:37Z","timestamp":1465602877000},"page":"3044-3046","source":"Crossref","is-referenced-by-count":42,"title":["<i>Meshable<\/i>\n                    : searching PubMed abstracts by utilizing MeSH and MeSH-derived topical terms"],"prefix":"10.1093","volume":"32","author":[{"given":"Sun","family":"Kim","sequence":"first","affiliation":[{"name":"National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lana","family":"Yeganova","sequence":"additional","affiliation":[{"name":"National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"W. John","family":"Wilbur","sequence":"additional","affiliation":[{"name":"National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2016,6,10]]},"reference":[{"key":"2023020113471130400_btw331-B1","author":"Aletras","year":"2013"},{"key":"2023020113471130400_btw331-B2","doi-asserted-by":"crossref","first-page":"S6","DOI":"10.1186\/2041-1480-3-S3-S6","article-title":"Thematic clustering of text documents using an EM-based approach","volume":"3","author":"Kim","year":"2012","journal-title":"J. Biomed. Semant"},{"key":"2023020113471130400_btw331-B3","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1186\/s12859-015-0487-2","article-title":"Identifying named entities from PubMed for enriching semantic categories","volume":"16","author":"Kim","year":"2015","journal-title":"BMC Bioinformtics"},{"key":"2023020113471130400_btw331-B4","author":"Kim","year":"2015"},{"key":"2023020113471130400_btw331-B5","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1002\/1097-4571(2000)9999:9999<::AID-ASI1588>3.0.CO;2-7","article-title":"Corpus-based statistical screening for content-bearing terms","volume":"52","author":"Kim","year":"2001","journal-title":"J. Am. Soc. Inform. Sci. 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Inform"},{"key":"2023020113471130400_btw331-B11","author":"Wilbur","year":"2002"},{"key":"2023020113471130400_btw331-B12","author":"Zhu","year":"2009"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/19\/3044\/49021708\/bioinformatics_32_19_3044.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/19\/3044\/49021708\/bioinformatics_32_19_3044.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T18:51:39Z","timestamp":1675277499000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/32\/19\/3044\/2196386"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,6,10]]},"references-count":12,"journal-issue":{"issue":"19","published-print":{"date-parts":[[2016,10,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw331","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2016,10,1]]},"published":{"date-parts":[[2016,6,10]]}}}