DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques

DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques

Abstract In silico prediction of drug–target interactions is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. However, developing such computational methods is not an easy task, but is much neede...

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Bibliographic Details
Main Authors: Maha A. Thafar, Rawan S. Olayan, Haitham Ashoor, Somayah Albaradei, Vladimir B. Bajic, Xin Gao, Takashi Gojobori, Magbubah Essack
Format: Article
Language:English
Published: BMC 2020-06-01
Series:Journal of Cheminformatics
Subjects:
Drug repositioning
Drug–target interaction
Machine learning
Graph embedding
Heterogenous network
Similarity-based
Online Access:http://link.springer.com/article/10.1186/s13321-020-00447-2

Internet

http://link.springer.com/article/10.1186/s13321-020-00447-2

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