{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:21:59Z","timestamp":1773415319473,"version":"3.50.1"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"18","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":1490,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,9,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Event extraction using expressive structured representations has been a significant focus of recent efforts in biomedical information extraction. However, event extraction resources and methods have so far focused almost exclusively on molecular-level entities and processes, limiting their applicability.<\/jats:p>\n               <jats:p>Results: We extend the event extraction approach to biomedical information extraction to encompass all levels of biological organization from the molecular to the whole organism. We present the ontological foundations, target types and guidelines for entity and event annotation and introduce the new multi-level event extraction (MLEE) corpus, manually annotated using a structured representation for event extraction. We further adapt and evaluate named entity and event extraction methods for the new task, demonstrating that both can be achieved with performance broadly comparable with that for established molecular entity and event extraction tasks.<\/jats:p>\n               <jats:p>Availability: The resources and methods introduced in this study are available from http:\/\/nactem.ac.uk\/MLEE\/.<\/jats:p>\n               <jats:p>Contact: \u00a0pyysalos@cs.man.ac.uk<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts407","type":"journal-article","created":{"date-parts":[[2012,9,7]],"date-time":"2012-09-07T20:35:22Z","timestamp":1347050122000},"page":"i575-i581","source":"Crossref","is-referenced-by-count":112,"title":["Event extraction across multiple levels of biological organization"],"prefix":"10.1093","volume":"28","author":[{"given":"Sampo","family":"Pyysalo","sequence":"first","affiliation":[{"name":"1 National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK"}]},{"given":"Tomoko","family":"Ohta","sequence":"additional","affiliation":[{"name":"1 National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK"}]},{"given":"Makoto","family":"Miwa","sequence":"additional","affiliation":[{"name":"1 National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK"}]},{"given":"Han-Cheol","family":"Cho","sequence":"additional","affiliation":[{"name":"2 Department of Computer Science, University of Tokyo, Tokyo, Japan"}]},{"given":"Jun'ichi","family":"Tsujii","sequence":"additional","affiliation":[{"name":"3 Microsoft Research Asia, Beijing, China"}]},{"given":"Sophia","family":"Ananiadou","sequence":"additional","affiliation":[{"name":"1 National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK"}]}],"member":"286","published-online":{"date-parts":[[2012,9,3]]},"reference":[{"key":"2023012513060596800_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 Biotechnol."},{"key":"2023012513060596800_B2","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene ontology: tool for the unification of biology","volume":"25","author":"Ashburner","year":"2000","journal-title":"Nat. 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