ArticleJournal of biomedical semantics2011
Event extraction for DNA methylation.
Article in Journal of biomedical semantics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A transfer learning model with multi-source domains for biomedical event trigger extraction.BMC genomics · 2021Article
- Overview of the Cancer Genetics and Pathway Curation tasks of BioNLP Shared Task 2013.BMC bioinformatics · 2015Article
- Adaptable, high recall, event extraction system with minimal configuration.BMC bioinformatics · 2015Article
- Wide coverage biomedical event extraction using multiple partially overlapping corpora.BMC bioinformatics · 2013Article
- Event extraction across multiple levels of biological organization.Bioinformatics (Oxford, England) · 2012Article
- Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011.BMC bioinformatics · 2012Article
- MeInfoText 2.0: gene methylation and cancer relation extraction from biomedical literature.BMC bioinformatics · 2011Article
- An analysis of gene/protein associations at PubMed scale.Journal of biomedical semantics · 2011Article
- Towards mature use of semantic resources for biomedical analyses.Journal of biomedical semantics · 2011Article
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4 authors.
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Abstract
backgroundWe consider the task of automatically extracting DNA methylation events from the biomedical domain literature. DNA methylation is a key mechanism of epigenetic control of gene expression and implicated in many cancers, but there has been little study of automatic information extraction for DNA methylation.
resultsWe present an annotation scheme for DNA methylation following the representation of the BioNLP shared task on event extraction, select a set of 200 abstracts including a representative sample of all PubMed citations relevant to DNA methylation, and introduce manual annotation for this corpus marking nearly 3000 gene/protein mentions and 1500 DNA methylation and demethylation events. We retrain a state-of-the-art event extraction system on the corpus and find that automatic extraction of DNA methylation events, the methylated genes, and their methylation sites can be performed at 78% precision and 76% recall.
conclusionsOur results demonstrate that reliable extraction methods for DNA methylation events can be created through corpus annotation and straightforward retraining of a general event extraction system. The introduced resources are freely available for use in research from the GENIA project homepage http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA.
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