Multiple kernels learning-based biological entity relationship extraction method.

Journal: Journal of biomedical semantics
Published Date:

Abstract

BACKGROUND: Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the most authoritative textual database in the field of biomedicine, and follow an exponential growth over time. This frantic expansion of the biomedical literature can often be difficult to absorb or manually analyze. Thus efficient and automated search engines are necessary to efficiently explore the biomedical literature using text mining techniques.

Authors

  • Xu Dongliang
    School of Mechanical, Electrical and Information Engineering, ShanDong University, WenHua West Road, WeiHai, 264209, China.
  • Pan Jingchang
    School of Mechanical, Electrical and Information Engineering, ShanDong University, WenHua West Road, WeiHai, 264209, China. pjc@sdu.edu.cn.
  • Wang Bailing
    School of Computer Science and Technology, Harbin Institute of Technology, WenHua West Road, WeiHai, 264209, China.