Combining NLP and probabilistic categorisation for document and term selection for Swiss-Prot medical annotation

Bioinformatics

Volumn 19, Issue SUPPL. 1, 2003, Pages

  Dobrokhotov, Pavel B ^a   Goutte, Cyril ^b   Veuthey, Anne Lise ^a   Gaussier, Eric ^b  

^a SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

^b XEROX RESEARCH CENTRE EUROPE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; CLASSIFICATION; CONFERENCE PAPER; MEDICAL LITERATURE; MEDLINE; PRIORITY JOURNAL; PROBABILITY; SWISS-PROT; ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; COMPARATIVE STUDY; DOCUMENTATION; EVALUATION; GENETICS; METHODOLOGY; NATURAL LANGUAGE PROCESSING; PROTEIN DATABASE; PUBLICATION; STATISTICAL MODEL; VALIDATION STUDY;

PROTEIN;

ABSTRACTING AND INDEXING; ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATABASES, PROTEIN; DOCUMENTATION; MODELS, STATISTICAL; NATURAL LANGUAGE PROCESSING; PATTERN RECOGNITION, AUTOMATED; PERIODICALS; PROTEINS; PUBMED;

EID: 4944257920     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btg1011     Document Type: Conference Paper

References (6)

1. Boeckmann, B. et al. (2003) The SWISS-PROT protein knowledge-base and its supplement TrEMBL in 2003. Nucleic Acids Res., 31, 365-370.
2. Dobrokhotov, P.B. et al. (2003) A probabilistic information retrieval approach to medical annotation in Swiss-Prot. Proc. MIE2003, (to appear).
3. Gaussier, E., Goutte, C., Popat, K. and Chen, F. (2002) A hierarchical model for clustering and categorising documents. In Crestani, F., Girolami, M. and van Rijsbergen, C.J. (eds), Advances in Information Retrieval. Springer, Berlin, pp. 229-247.
4. Hagège, C., Sandor, A. and Schiller, A. (2002) Linguistic processing of biomedical texts. In Ranchod, E. and Mamede, N.J. (eds), Advances in Natural Language Processing. Springer, Berlin, pp. 197-208.
5. Marcotte, E.M. et al. (2001) Mining literature for protein-protein interactions. Bioinformatics, 17, 359-363.
6. Wilbur, J.W. (2000) Boosting Naïve Bayesian Learning on a Large Subset of MEDLINE. Proc. AMIA Symp, 918-922.