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Genome Informatics 14: 699-700 (2003) 699 Extracting Information on Protein-Protein Interactions  (Make Corrections)  
from Biological Literature Based on Machine Learning Approaches Kazunari...



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Abstract: this paper, we proposed several machine learning approaches to extracting information on proteinprotein interactions from biological literature. Experimental results show that the classifier based on SVM can provide the highest accuracy in this type of task. In future work, we plan to explore the characteristics of each machine learning approach in more detail and refine our approach to develop an information extraction system with even higher accuracy (Update)

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BibTeX entry:   (Update)

@misc{ literature-genome,
  author = "From Biological Literature",
  title = "Genome Informatics 14: 699--700 (2003) 699 Extracting Information on Protein-Protein
    Interactions",
  url = "citeseer.ist.psu.edu/704053.html" }
Citations (may not include all citations):
2177   Programs for Machine Learning (context) - Quinlan - 1993
1291   The Nature of Statistical Learning Theory (context) - Vapnik - 1995
550   Parallel Distributed Processing (context) - Rumelhart, McClelland - 1986
286   Nearest neighbor pattern classification (context) - Cover, Hart - 1967
25   Automatic extraction of protein interactions from scientific.. - Thomas, Milward et al. - 2000
24   Identifying the interaction between genes and gene products .. - Sekimizu, Park et al. - 1998
15   GENIES: a natural-language processing system for the extract.. (context) - Friedman, Kra et al. - 2001
13   Event Extraction from Biomedical Papers using a Full Parser (context) - Yakushiji, Tateisi et al. - 2001
1   the Pacific Symposium on Biocomputing (context) - Humphreys, Demetriou et al. - 2000
1   The potential use of SUISEKI as a protein interaction discov.. (context) - Blaschke, Valencia - 2001
1   ofthe Pacific Symposium on Biocomputing (context) - Ding, Berleant - 2002
http://fasta.bioch.virginia.edu/fasta_www/

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