Automatic Extraction of Proteins and Their Interactions from Biological Text

  • Kiho Hong
  • Junhyung Park
  • Jihoon Yang
  • Eunok Paek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3735)


Text mining techniques have been proposed for extracting protein names and their interactions from biological text. First, we have made improvements on existing methods for handling single word protein names consisting of characters, special symbols, and numbers. Second, compound word protein names are also extracted using conditional probabilities of the occurrences of neighboring words. Third, interactions are extracted based on Bayes theorem over discriminating verbs that represent the interactions of proteins. Experimental results demonstrate the feasibility of our approach with improved performance in terms of accuracy and F-measure, requiring significantly less amount of computational time.


Automatic Extraction Word Class Past Participle Roman Letter GENIA Corpus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Kiho Hong
    • 1
  • Junhyung Park
    • 2
  • Jihoon Yang
    • 2
  • Eunok Paek
    • 3
  1. 1.IT Agent Research LabLSIS R&D CenterKyungki-DoKorea
  2. 2.Department of Computer Science and Interdisciplinary Program of Integrated BiotechnologySogang UniversitySeoulKorea
  3. 3.Department of Mechanical and Information EngineeringThe University of SeoulSeoulKorea

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