{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T10:16:43Z","timestamp":1771237003485,"version":"3.50.1"},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2020,8,18]],"date-time":"2020-08-18T00:00:00Z","timestamp":1597708800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UK Medical Research Council Integrative Epidemiology Unit","award":["MC_UU_00011\/4"],"award-info":[{"award-number":["MC_UU_00011\/4"]}]},{"name":"Cancer Research UK Integrative Cancer Epidemiology Programme","award":["C18281\/A19169"],"award-info":[{"award-number":["C18281\/A19169"]}]},{"name":"University of Bristol. T.R.G. holds a fellowship from the Alan Turing Institute"},{"name":"GlaxoSmithKline and Biogen for unrelated research"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,1]]},"abstract":"ABSTRACT<\/jats:title>\n \n Summary<\/jats:title>\n The field of literature-based discovery is growing in step with the volume of literature being produced. From modern natural language processing algorithms to high quality entity tagging, the methods and their impact are developing rapidly. One annotation object that arises from these approaches, the subject\u2013predicate\u2013object triple, is proving to be very useful in representing knowledge. We have implemented efficient search methods and an application programming interface, to create fast and convenient functions to utilize triples extracted from the biomedical literature by SemMedDB. By refining these data, we have identified a set of triples that focus on the mechanistic aspects of the literature, and provide simple methods to explore both enriched triples from single queries, and overlapping triples across two query lists.<\/jats:p>\n <\/jats:sec>\n \n Availability and Implementation<\/jats:title>\n https:\/\/melodi-presto.mrcieu.ac.uk\/.<\/jats:p>\n <\/jats:sec>\n \n Supplementary information<\/jats:title>\n Supplementary data are available at Bioinformatics online.<\/jats:p>\n <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa726","type":"journal-article","created":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T14:57:06Z","timestamp":1597157826000},"page":"583-585","source":"Crossref","is-referenced-by-count":22,"title":["MELODI Presto: a fast and agile tool to explore semantic triples derived from biomedical literature"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7328-4233","authenticated-orcid":false,"given":"Benjamin","family":"Elsworth","sequence":"first","affiliation":[{"name":"MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol , Bristol BS8 2BN, UK"}]},{"given":"Tom R","family":"Gaunt","sequence":"additional","affiliation":[{"name":"MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol , Bristol BS8 2BN, UK"}]}],"member":"286","published-online":{"date-parts":[[2020,8,18]]},"reference":[{"key":"2023051706075168600_btaa726-B1","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1093\/ije\/dyx251","article-title":"MELODI: mining enriched literature objects to derive intermediates","volume":"47","author":"Elsworth","year":"2018","journal-title":"Int. J. Epidemiol"},{"key":"2023051706075168600_btaa726-B2","author":"Elsworth","year":"2020"},{"key":"2023051706075168600_btaa726-B3","doi-asserted-by":"crossref","first-page":"3158","DOI":"10.1093\/bioinformatics\/bts591","article-title":"SemMedDB: a PubMed-scale repository of biomedical semantic predications","volume":"28","author":"Kilicoglu","year":"2012","journal-title":"Bioinformatics"},{"key":"2023051706075168600_btaa726-B4","author":"Koroleva","year":"2020"},{"key":"2023051706075168600_btaa726-B5","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1016\/j.jbi.2003.11.003","article-title":"The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text","volume":"36","author":"Rindflesch","year":"2003","journal-title":"J. Biomed. Inform"},{"key":"2023051706075168600_btaa726-B6","article-title":"AGATHA: automatic graph-mining and transformer based hypothesis generation approach","author":"Sybrandt","year":"2020","journal-title":"arXiv:2002.05635"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa726\/34051619\/btaa726.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/4\/583\/50359857\/btaa726.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/4\/583\/50359857\/btaa726.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,17]],"date-time":"2023-05-17T06:12:13Z","timestamp":1684303933000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/37\/4\/583\/5893950"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,8,18]]},"references-count":6,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,5,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa726","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2021,2,15]]},"published":{"date-parts":[[2020,8,18]]}}}