An entity tagger for recognizing acquired genomic variations in cancer literature
VTag is an application for identifying the type, genomic location and genomic state-change of acquired genomic aberrations described in text. The application uses a machine learning technique called conditional random fields. VTag was tested with 345 training and 200 evaluation documents pertaining...
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Veröffentlicht in: | Bioinformatics 2004-11, Vol.20 (17), p.3249-3251 |
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Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | VTag is an application for identifying the type, genomic location and genomic state-change of acquired genomic aberrations described in text. The application uses a machine learning technique called conditional random fields. VTag was tested with 345 training and 200 evaluation documents pertaining to cancer genetics. Our experiments resulted in 0.8541 precision, 0.7870 recall and 0.8192 F-measure on the evaluation set. Availability: The software is available at http://www.cis.upenn.edu/group/datamining/software_dist/biosfier/. |
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ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/bth350 |