{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T15:21:02Z","timestamp":1777648862040,"version":"3.51.4"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"20","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,10,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: The abundance of biomedical literature has attracted significant interest in novel methods to automatically extract biomedical relations from the literature. Until recently, most research was focused on extracting binary relations such as protein\u2013protein interactions and drug\u2013disease relations. However, these binary relations cannot fully represent the original biomedical data. Therefore, there is a need for methods that can extract fine-grained and complex relations known as biomedical events.<\/jats:p>\n               <jats:p>Results: In this article we propose a novel method to extract biomedical events from text. Our method consists of two phases. In the first phase, training data are mapped into structured representations. Based on that, templates are used to extract rules automatically. In the second phase, extraction methods are developed to process the obtained rules. When evaluated against the Genia event extraction abstract and full-text test datasets (Task 1), we obtain results with F-scores of 52.34 and 53.34, respectively, which are comparable to the state-of-the-art systems. Furthermore, our system achieves superior performance in terms of computational efficiency.<\/jats:p>\n               <jats:p>Availability: Our source code is available for academic use at http:\/\/dl.dropbox.com\/u\/10256952\/BioEvent.zip<\/jats:p>\n               <jats:p>Contact: bqchinh@gmail.com<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts487","type":"journal-article","created":{"date-parts":[[2012,8,2]],"date-time":"2012-08-02T05:21:57Z","timestamp":1343884917000},"page":"2654-2661","source":"Crossref","is-referenced-by-count":22,"title":["A robust approach to extract biomedical events from literature"],"prefix":"10.1093","volume":"28","author":[{"given":"Quoc-Chinh","family":"Bui","sequence":"first","affiliation":[{"name":"Computational Science, Informatics Institute, Faculty of Science, University of Amsterdam, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter M.A.","family":"Sloot","sequence":"additional","affiliation":[{"name":"Computational Science, Informatics Institute, Faculty of Science, University of Amsterdam, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,8,1]]},"reference":[{"key":"2023012513135104900_bts487-B1","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1016\/j.tibtech.2010.04.005","article-title":"Event extraction for systems biology by text mining the literature","volume":"28","author":"Ananiadou","year":"2010","journal-title":"Trends in Biotechnol."},{"key":"2023012513135104900_bts487-B2","first-page":"10","article-title":"Extracting complex biological events with rich graph-based feature sets","author":"Bj\u00f6rne","year":"2009"},{"key":"2023012513135104900_bts487-B3","first-page":"26, i382","article-title":"Complex event extraction at PubMed scale","author":"Bj\u00f6rne","year":"2010","journal-title":"Bioinformatics (Oxford, England)"},{"key":"2023012513135104900_bts487-B4","first-page":"183","article-title":"Generalizing biomedical event extraction","author":"Bj\u00f6rne","year":"2011"},{"key":"2023012513135104900_bts487-B5","first-page":"143","article-title":"Extracting biological events from text using simple syntactic patterns","author":"Bui","year":"2011"},{"key":"2023012513135104900_bts487-B6","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1186\/1471-2105-11-101","article-title":"Extracting causal relations on HIV drug resistance from literature","volume":"11","author":"Bui","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"2023012513135104900_bts487-B7"},{"key":"2023012513135104900_bts487-B8","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1111\/j.1467-8640.2011.00405.x","article-title":"High-precision biological event extraction: effects of system and of data","volume":"27","author":"Cohen","year":"2011","journal-title":"Comput. Intelligence"},{"key":"2023012513135104900_bts487-B9","first-page":"50","article-title":"High-precision biological event extraction with a concept recognizer","author":"Cohen","year":"2009"},{"key":"2023012513135104900_bts487-B10","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1186\/1471-2105-11-492","article-title":"The structural and content aspects of abstracts versus bodies of full text journal articles are different","volume":"11","author":"Cohen","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"2023012513135104900_bts487-B11","doi-asserted-by":"crossref","first-page":"S5","DOI":"10.1186\/1471-2105-7-S3-S5","article-title":"A critical review of PASBio\u2019s argument structures for biomedical verbs","volume":"7","author":"Cohen","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2023012513135104900_bts487-B12","doi-asserted-by":"crossref","first-page":"S11","DOI":"10.1186\/1471-2105-9-S9-S11","article-title":"Large-scale directional relationship extraction and resolution","volume":"9","author":"Giles","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2023012513135104900_bts487-B13","first-page":"173","article-title":"Adapting a general semantic interpretation approach to biological event extraction","author":"Kilicoglu","year":"2011"},{"key":"2023012513135104900_bts487-B14"},{"key":"2023012513135104900_bts487-B15"},{"key":"2023012513135104900_bts487-B16","first-page":"7","article-title":"Overview of Genia Event Task in BioNLP Shared Task 2011","author":"Kim","year":"2011"},{"key":"2023012513135104900_bts487-B17","first-page":"164","article-title":"From Graphs to Events: a subgraph matching approach for information extraction from biomedical text","author":"Liu","year":"2011"},{"key":"2023012513135104900_bts487-B18","first-page":"41","article-title":"Event extraction as dependency parsing for BioNLP 2011","author":"Mcclosky","year":"2011"},{"key":"2023012513135104900_bts487-B19","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/bts237","article-title":"Boosting automatic event extraction from the literature using domain adaptation and coreference resolution","author":"Miwa","year":"2012","journal-title":"Bioinformatics"},{"key":"2023012513135104900_bts487-B20","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1142\/S0219720010004586","article-title":"Event extraction with complex event classification using rich features","volume":"08","author":"Miwa","year":"2010","journal-title":"J. Bioinform. Comput. Biol."},{"key":"2023012513135104900_bts487-B21"},{"key":"2023012513135104900_bts487-B22"},{"key":"2023012513135104900_bts487-B23","first-page":"813","article-title":"Joint Inference for Knowledge Extraction from Biomedical Literature","author":"Poon","year":"2010"},{"key":"2023012513135104900_bts487-B24","first-page":"155","article-title":"MSR-NLP Entry in BioNLP Shared Task 2011","author":"Quirk","year":"2011"},{"key":"2023012513135104900_bts487-B25","first-page":"46","article-title":"Robust biomedical event extraction with dual decomposition and minimal domain adaptation","author":"Riedel","year":"2011"},{"key":"2023012513135104900_bts487-B26","first-page":"1","article-title":"Fast and robust joint models for biomedical event extraction","author":"Riedel","year":"2011"},{"key":"2023012513135104900_bts487-B27","doi-asserted-by":"crossref","first-page":"S1","DOI":"10.1186\/1471-2105-12-S2-S1","article-title":"A linguistic rule-based approach to extract drug-drug interactions from pharmacological documents","volume":"12","author":"Segura-Bedmar","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2023012513135104900_bts487-B28","first-page":"i547","article-title":"Discovering drug-drug interactions: a text-mining and reasoning approach based on properties of drug metabolism","volume":"26","author":"Tari","year":"2010","journal-title":"Bioinformatics (Oxford, England)"},{"key":"2023012513135104900_bts487-B29","first-page":"36","article-title":"Biomedical event extraction from abstracts and full papers using search-based structured prediction","author":"Vlachos","year":"2011"},{"key":"2023012513135104900_bts487-B30","doi-asserted-by":"crossref","first-page":"2025","DOI":"10.1093\/bioinformatics\/btr327","article-title":"Question answering systems in biology and medicine\u2014the time is now","volume":"27","author":"Wren","year":"2011","journal-title":"Bioinformatics (Oxford, England)"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/28\/20\/2654\/48872896\/bioinformatics_28_20_2654.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/28\/20\/2654\/48872896\/bioinformatics_28_20_2654.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T19:14:40Z","timestamp":1674674080000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/28\/20\/2654\/202303"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,8,1]]},"references-count":30,"journal-issue":{"issue":"20","published-print":{"date-parts":[[2012,10,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bts487","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2012,10,15]]},"published":{"date-parts":[[2012,8,1]]}}}