Machine learning approaches and databases for prediction of drug–target interaction: a survey paper

• Published in: Briefings in bioinformatics Vol. 22; no. 1; pp. 247 - 269
• Main Authors: Bagherian, Maryam, Sabeti, Elyas, Wang, Kai, Sartor, Maureen A, Nikolovska-Coleska, Zaneta, Najarian, Kayvan
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 18.01.2021; Oxford Publishing Limited (England)
• Subjects: Computational Biology - methods; Databases, Factual; Drug Discovery - methods; Humans; Learning algorithms; Machine Learning; Predictions; Review; Therapeutic targets; DTI database; DTI software; drug–target interaction prediction; Machine learning

Abstract The task of predicting the interactions between drugs and targets plays a key role in the process of drug discovery. There is a need to develop novel and efficient prediction approaches in order to avoid costly and laborious yet not-always-deterministic experiments to determine drug–target...