Extracting Protein-Protein Interaction Information from Biomedical Text with SVM

  • Authors:

  • Tomohiro Mitsumori;Masaki Murata;Yasushi Fukuda;Kouichi Doi;Hirohumi Doi

  • Affiliations:

  • The authors are with the Graduate School of the Information Science, Nara Institute of Science and Technology, Ikoma-shi, 630-0101 Japan. E-mail: mitsumor@is.naist.jp,;The author is with the National Institute of Information and Communications Technology, Kyoto-fu, 619-0289 Japan.,;The author is with the Sony-Kihara Research Center Inc., Tokyo, 141-0022 Japan.;The authors are with the Graduate School of the Information Science, Nara Institute of Science and Technology, Ikoma-shi, 630-0101 Japan. E-mail: mitsumor@is.naist.jp,;The authors are with the Graduate School of the Information Science, Nara Institute of Science and Technology, Ikoma-shi, 630-0101 Japan. E-mail: mitsumor@is.naist.jp,

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2006

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Abstract

Automated information extraction systems from biomedical text have been reported. Some systems are based on manually developed rules or pattern matching. Manually developed rules are specific for analysis, however, new rules must be developed for each new domain. Although the corpus must be developed by human effort, a machine-learning approach automatically learns the rules from the corpus. In this article, we present a system for automatically extracting protein-protein interaction information from biomedical text with support vector machines (SVMs). We describe the performance of our system and compare its ability to extract protein-protein interaction information with that of other systems.