A new method for prioritizing drug repositioning candidates extracted by literature-based discovery

Majid Rastegar-Mojarad, Ravikumar Komandur Elayavilli, Dingcheng Li, Rashmi Prasad, Hongfang D Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Drug repositioning has been a topic of great attention to researchers and pharmaceutical companies due to its significant impact on the cost of drug discovery. There are several approaches to identify potentially novel drug candidates through repurposing. Literature mining has played a critical role in mining such information from scientific articles. In this paper, we used drug-gene and gene-disease semantic predications extracted from Medline abstracts to generate a list of potential drug-disease pairs. We further ranked the generated pairs, by assigning scores based on the predicates that qualify drug-gene and gene-disease relationships. On comparing the top-ranked drug-disease pairs against the Comparative Toxicogenomics Database (CTD), a curated database for drug-disease relations, we found that a significant percentage of top ranked pairs appeared in CTD. Co-occurrence of these high-ranked pairs in Medline abstracts further improves the confidence in our approach to rank the inferred drug-disease relations higher in the list. Finally, manual evaluation of top ten pairs ranked by our approach revealed that nine of them have some biological significance based on expert judgment.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages669-674
Number of pages6
ISBN (Print)9781467367981
DOIs
StatePublished - Dec 16 2015
EventIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 - Washington, United States
Duration: Nov 9 2015Nov 12 2015

Other

OtherIEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
CountryUnited States
CityWashington
Period11/9/1511/12/15

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Keywords

  • Drug repositioning
  • Literature-based discovery
  • Semantic Predication

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Health Informatics
  • Biomedical Engineering

Cite this

Rastegar-Mojarad, M., Elayavilli, R. K., Li, D., Prasad, R., & Liu, H. D. (2015). A new method for prioritizing drug repositioning candidates extracted by literature-based discovery. In Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015 (pp. 669-674). [7359766] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2015.7359766