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Drug Discov Today. 2017 Apr;22(4):615-619. doi: 10.1016/j.drudis.2016.10.008. Epub 2016 Oct 22.

Drug repurposing by integrated literature mining and drug-gene-disease triangulation.

Author information

1
Max-Planck Institute for Informatics, Saarbrücken, Germany; Cluster of Excellence for Multimodal Computing and Interaction, Saarland University, Saarbrücken, Germany.
2
School of Computer Science and Technology, ShanDong University, Qingdao, China.
3
Stanford Center for Biomedical Research, Stanford University, Stanford, CA, USA.
4
Max-Planck Institute for Informatics, Saarbrücken, Germany; Institute of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark. Electronic address: jan.baumbach@imada.sdu.dk.

Abstract

Drug design is expensive, time-consuming and becoming increasingly complicated. Computational approaches for inferring potentially new purposes of existing drugs, referred to as drug repositioning, play an increasingly important part in current pharmaceutical studies. Here, we first summarize recent developments in computational drug repositioning and introduce the utilized data sources. Afterwards, we introduce a new data fusion model based on n-cluster editing as a novel multi-source triangulation strategy, which was further combined with semantic literature mining. Our evaluation suggests that utilizing drug-gene-disease triangulation coupled to sophisticated text analysis is a robust approach for identifying new drug candidates for repurposing.

PMID:
27780789
DOI:
10.1016/j.drudis.2016.10.008
[Indexed for MEDLINE]

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