From Biomedical Literature to Knowledge: Mining Protein-Protein Interactions

  • Deyu Zhou
  • Yulan He
  • Chee Keong Kwoh
Part of the Studies in Computational Intelligence book series (SCI, volume 151)


To date, more than 16 million citations of published articles in biomedical domain are available in the MEDLINE database. These articles describe the new discoveries which accompany a tremendous development in biomedicine during the last decade. It is crucial for biomedical researchers to retrieve and mine some specific knowledge from the huge quantity of published articles with high efficiency. Researchers have been engaged in the development of text mining tools to find knowledge such as protein-protein interactions, which are most relevant and useful for specific analysis tasks. This chapter provides a road map to the various information extraction methods in biomedical domain, such as protein name recognition and discovery of protein-protein interactions. Disciplines involved in analyzing and processing unstructured-text are summarized. Current work in biomedical information extracting is categorized. Challenges in the field are also presented and possible solutions are discussed.


Support Vector Machine Hide Markov Model Natural Language Processing Information Extraction Biomedical Literature 
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 2008

Authors and Affiliations

  • Deyu Zhou
    • 1
  • Yulan He
    • 1
  • Chee Keong Kwoh
    • 2
  1. 1.Informatics Research CentreThe University of ReadingReadingUK
  2. 2.School of Computer EngineeringNanyang Technological UniversitySingapore

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