Extracting Regulatory Gene Expression Networks From Pubmed

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We present an approach using syntactosemantic rules for the extraction of relational information from biomedical abstracts. The results show that by overcoming the hurdle of technical terminology, high precision results can be . From abstracts related to baker's yeast, we manage to extract a regulatory network comprised of 441 relations from 58,664 abstracts with an accuracy of 83

Jasmin Saric, Lars Juhl Jensen, Peer Bork, Rossitz

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Added	30 Oct 2010
Updated	30 Oct 2010
Type	Conference
Year	2004
Where	ACL
Authors	Jasmin Saric, Lars Juhl Jensen, Peer Bork, Rossitza Ouzounova, Isabel Rojas

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Extracting Regulatory Gene Expression Networks From Pubmed

ACL 2004 | ACL 2007 | Biomedical Abstracts | Molecular Biology Abstracts | Retrained Part-of-speech Tagger |

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