Literature DB >> 15359426

Bioie: retargetable information extraction and ontological annotation of biological interactions from the literature.

Jung-Jae Kim1, Jong C Park.   

Abstract

The need for extracting general biological interactions of arbitrary types from the rapidly growing volume of the biomedical literature is drawing increased attention, while the need for this much diversity also requires both a robust treatment of complex linguistic phenomena and a method to consistently characterize the results. We present a biomedical information extraction system, BioIE, to address both of these needs by utilizing a full-fledged English grammar formalism, or a combinatory categorial grammar, and by annotating the results with the terms of Gene Ontology, which provides a common and controlled vocabulary. BioIE deals with complex linguistic phenomena such as coordination, relative structures, acronyms, appositive structures, and anaphoric expressions. In order to deal with real-world syntactic variations of ontological terms, BioIE utilizes the syntactic dependencies between words in sentences as well, based on the observation that the component words in an ontological term usually appear in a sentence with known patterns of syntactic dependencies.

Mesh:

Substances:

Year:  2004        PMID: 15359426     DOI: 10.1142/s0219720004000739

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  4 in total

1.  Collaborative text-annotation resource for disease-centered relation extraction from biomedical text.

Authors:  C Cano; T Monaghan; A Blanco; D P Wall; L Peshkin
Journal:  J Biomed Inform       Date:  2009-02-14       Impact factor: 6.317

2.  Mining experimental evidence of molecular function claims from the literature.

Authors:  Colleen E Crangle; J Michael Cherry; Eurie L Hong; Alex Zbyslaw
Journal:  Bioinformatics       Date:  2007-10-17       Impact factor: 6.937

3.  Resolving anaphoras for the extraction of drug-drug interactions in pharmacological documents.

Authors:  Isabel Segura-Bedmar; Mario Crespo; César de Pablo-Sánchez; Paloma Martínez
Journal:  BMC Bioinformatics       Date:  2010-04-16       Impact factor: 3.169

4.  GOAnnotator: linking protein GO annotations to evidence text.

Authors:  Francisco M Couto; Mário J Silva; Vivian Lee; Emily Dimmer; Evelyn Camon; Rolf Apweiler; Harald Kirsch; Dietrich Rebholz-Schuhmann
Journal:  J Biomed Discov Collab       Date:  2006-12-20
  4 in total

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