Biomedical relation extraction:from binary to complex


Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Additional Information: Copyright © 2014 Deyu Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Uncontrolled Keywords: Applied Mathematics,Modelling and Simulation,Biochemistry, Genetics and Molecular Biology(all),Medicine(all),Immunology and Microbiology(all)
Publication ISSN: 1748-6718
Last Modified: 15 Apr 2024 07:13
Date Deposited: 02 Jul 2015 12:05
Full Text Link: http://www.hind ... mm/2014/298473/
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2014-08-19
Authors: Zhou, Deyu
Zhong, Dayou
He, Yulan (ORCID Profile 0000-0003-3948-5845)



Version: Published Version

License: Creative Commons Attribution

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