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Using the OntoGene pipeline for the triage task of BioCreative 2012
Institute of Computational Linguistics, University of Zurich, Switzerland.ORCID iD: 0000-0001-5718-5462
Institute of Computational Linguistics, University of Zurich, Switzerland.
Institute of Computational Linguistics, University of Zurich, Switzerland.
Institute of Computational Linguistics, University of Zurich, Switzerland.
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2013 (English)In: Database: The Journal of Biological Databases and Curation, ISSN 1758-0463, E-ISSN 1758-0463, ISSN 1758-0463Article in journal (Refereed) Published
Abstract [en]

In this article, we describe the architecture of the OntoGene Relation mining pipeline and its application in the triage task of BioCreative 2012. The aim of the task is to support the triage of abstracts relevant to the process of curation of the Comparative Toxicogenomics Database. We use a conventional information retrieval system (Lucene) to provide a baseline ranking, which we then combine with information provided by our relation mining system, in order to achieve an optimized ranking. Our approach additionally delivers domain entities mentioned in each input document as well as candidate relationships, both ranked according to a confidence score computed by the system. This information is presented to the user through an advanced interface aimed at supporting the process of interactive curation. Thanks, in particular, to the high-quality entity recognition, the OntoGene system achieved the best overall results in the task.

Place, publisher, year, edition, pages
2013.
National Category
Bioinformatics (Computational Biology) Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:su:diva-93898DOI: 10.1093/database/bas053OAI: oai:DiVA.org:su-93898DiVA: diva2:649888
Available from: 2013-09-19 Created: 2013-09-19 Last updated: 2017-12-06Bibliographically approved

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Publisher's full texthttp://database.oxfordjournals.org/content/2013/bas053.abstract

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