A method for exploring implicit concept relatedness in biomedical knowledge network.

Journal: BMC bioinformatics
Published Date: Jul 19, 2016

Abstract

BACKGROUND: Biomedical information and knowledge, structural and non-structural, stored in different repositories can be semantically connected to form a hybrid knowledge network. How to compute relatedness between concepts and discover valuable but implicit information or knowledge from it effectively and efficiently is of paramount importance for precision medicine, and a major challenge facing the biomedical research community.

Authors

  • Tian Bai
    Key Laboratory of Bio-based Material Science & Technology (Northeast Forestry University), Ministry of Education, Harbin, China.
  • Leiguang Gong
    College of Computer Science and Technology, Jilin Univesity, 2699 Qianjin St, Changchun, China.
  • Ye Wang
    College of Computer Science and Technology, Jilin University, Changchun 130012, China.
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Casimir A Kulikowski
    Department of Computer Science, Rutgers, The State University of New Jersey, 2699 Qianjin St, Piscataway, NJ, USA.
  • Lan Huang

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