Extraction of genotype-phenotype-drug relationships from text: from entity recognition to bioinformatics application. - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Pacific Symposium on Biocomputing Année : 2010

Extraction of genotype-phenotype-drug relationships from text: from entity recognition to bioinformatics application.

Résumé

Advances in concept recognition and natural language parsing have led to the development of various tools that enable the identification of biomedical entities and relationships between them in text. The aim of the Genotype-Phenotype-Drug Relationship Extraction from Text workshop (or GPD-Rx workshop) is to examine the current state of art and discuss the next steps for making the extraction of relationships between biomedical entities integral to the curation and knowledge management workflow in Pharmacogenomics. The workshop will focus particularly on the extraction of Genotype-Phenotype, Genotype-Drug, and Phenotype-Drug relationships that are of interest to Pharmacogenomics. Extracting and structuring such text-mined relationships is a key to support the evaluation and the validation of multiple hypotheses that emerge from high throughput translational studies spanning multiple measurement modalities. In order to advance this agenda, it is essential that existing relationship extraction methods be compared to one another and that a community wide benchmark corpus emerges; against which future methods can be compared. The workshop aims to bring together researchers working on the automatic or semi-automatic extraction of relationships between biomedical entities from research literature in order to identify the key groups interested in creating such a benchmark.
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Dates et versions

inria-00549705 , version 1 (22-12-2010)

Identifiants

  • HAL Id : inria-00549705 , version 1
  • PUBMED : 19904832

Citer

Adrien Coulet, Nigam H. Shah, Lawrence Hunter, Chitta Barral, Russ B Altman. Extraction of genotype-phenotype-drug relationships from text: from entity recognition to bioinformatics application.. Pacific Symposium on Biocomputing, 2010, pp.485-7. ⟨inria-00549705⟩
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