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| Title: | EXTRACTION OF GENOTYPE-PHENOTYPE-DRUG RELATIONSHIPS FROM TEXT: FROM ENTITY RECOGNITION TO BIOINFORMATICS APPLICATION | |
| DOI No: | 10.1142/9789814295291_0051 | |
| Source: | BIOCOMPUTING 2010 (pp 485-487) | |
| Author(s): | ADRIEN COULET
Department of Genetics, Stanford University, Stanford, CA 94305, USA Department of Medicine, Stanford University, Stanford, CA 94305, USA NIGAM SHAH Department of Medicine, Stanford University, Stanford, CA 94305, USA LAWRENCE HUNTER Center for Computational Pharmacology, University of Colorado Denver School of Medicine, Aurora, CO 80045, USA CHITTA BARRAL Department of Computer Science and Engineering, Arizona State University, Tempe, AZ 85287, USA RUSS B. ALTMAN Department of Genetics, Stanford University, Stanford, CA 94305, USA Department of Bioengineering, Stanford University, Stanford, CA 94305, USA |
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| Abstract: | 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. | |
| Keywords: | NLP; Pharmacogenomics; Entity Recognition; Event Extraction; Genotype-Phenotype-Drug Relationships |
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| Full Text: | View full text in PDF format (835KB) | |
| TOC: | Back to Table of Contents | |
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