Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-24602
Schneider, G (2009). Detecting Protein-Protein Interactions in Biomedical Literature Using a Parser. In: Clematide, S; Klenner, M; Volk, M. Searching Answers. Münster, 109-118. ISBN 978-3-642-00381-3.
We describe the task of automatically detecting interactions between proteins in biomedical literature. We use a syntactic parser, a corpus annotated for proteins, and manual decisions as training material. After automatically parsing the GENIA corpus, which is manually annotated for proteins, all syntactic paths between proteins are extracted. These syntactic paths are manually disambiguated between meaningful paths and irrelevant paths. Meaningful paths are paths that express an interaction between the syntactically connected proteins, irrelevant paths are paths that do not convey any interaction. The resource created by these manual decisions is used in two ways. First, words that appear frequently inside a meaningful path are learnt using simple machine learning. Second, these resources are applied to the task of automatically detecting interactions between proteins in biomedical literature.
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|Item Type:||Book Section, not refereed, original work|
|Communities & Collections:||06 Faculty of Arts > Institute of Computational Linguistics
06 Faculty of Arts > English Department
|Dewey Decimal Classification:||000 Computer science, knowledge & systems
820 English & Old English literatures
|Uncontrolled Keywords:||IR, NLP, text mining, parsing, biomedicine|
|Deposited On:||23 Dec 2009 13:29|
|Last Modified:||09 Jul 2012 04:01|
|Funders:||Swiss National Science Fund, Grant 100014-118396/1|
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