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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2014-12-01
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Series: | Journal of Integrative Bioinformatics |
Online Access: | https://doi.org/10.1515/jib-2014-247 |
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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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1717768360963342336 |