Identifying interactions between chemical entities in biomedical text

Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, “Identifying Interactions between Chemical Entities” (IICE), to identify chemical interactions described in text. K...

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Main Authors: Lamurias Andre, Ferreira João D., Couto Francisco M.
Format: Article
Language:English
Published: De Gruyter 2014-12-01
Series:Journal of Integrative Bioinformatics
Online Access:https://doi.org/10.1515/jib-2014-247
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spelling doaj-6013eef79b0947f8b4ea899ffe1397df2021-09-06T19:40:31ZengDe GruyterJournal of Integrative Bioinformatics1613-45162014-12-0111311610.1515/jib-2014-247jib-2014-247Identifying interactions between chemical entities in biomedical textLamurias Andre0Ferreira João D.1Couto Francisco M.2LaSIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, 1749-016, Lisboa, PortugalLaSIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, 1749-016, Lisboa, PortugalLaSIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, 1749-016, Lisboa, PortugalInteractions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, “Identifying Interactions between Chemical Entities” (IICE), to identify chemical interactions described in text. Kernel-based Support Vector Machines first identify the interactions and then an ensemble classifier validates and classifies the type of each interaction. This relation extraction module was evaluated with the corpus released for the DDI Extraction task of SemEval 2013, obtaining results comparable to stateof- the-art methods for this type of task. We integrated this module with our chemical named entity recognition module and made the whole system available as a web tool at www.lasige.di.fc.ul.pt/webtools/iice.https://doi.org/10.1515/jib-2014-247
collection DOAJ
language English
format Article
sources DOAJ
author Lamurias Andre
Ferreira João D.
Couto Francisco M.
spellingShingle Lamurias Andre
Ferreira João D.
Couto Francisco M.
Identifying interactions between chemical entities in biomedical text
Journal of Integrative Bioinformatics
author_facet Lamurias Andre
Ferreira João D.
Couto Francisco M.
author_sort Lamurias Andre
title Identifying interactions between chemical entities in biomedical text
title_short Identifying interactions between chemical entities in biomedical text
title_full Identifying interactions between chemical entities in biomedical text
title_fullStr Identifying interactions between chemical entities in biomedical text
title_full_unstemmed Identifying interactions between chemical entities in biomedical text
title_sort identifying interactions between chemical entities in biomedical text
publisher De Gruyter
series Journal of Integrative Bioinformatics
issn 1613-4516
publishDate 2014-12-01
description Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, “Identifying Interactions between Chemical Entities” (IICE), to identify chemical interactions described in text. Kernel-based Support Vector Machines first identify the interactions and then an ensemble classifier validates and classifies the type of each interaction. This relation extraction module was evaluated with the corpus released for the DDI Extraction task of SemEval 2013, obtaining results comparable to stateof- the-art methods for this type of task. We integrated this module with our chemical named entity recognition module and made the whole system available as a web tool at www.lasige.di.fc.ul.pt/webtools/iice.
url https://doi.org/10.1515/jib-2014-247
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