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DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
2021
Journal of Cheminformatics
AbstractDrug–target interaction (DTI) prediction is a crucial step in drug discovery and repositioning as it reduces experimental validation costs if done right. Thus, developing in-silico methods to predict potential DTI has become a competitive research niche, with one of its main focuses being improving the prediction accuracy. Using machine learning (ML) models for this task, specifically network-based approaches, is effective and has shown great advantages over the other computational
doi:10.1186/s13321-021-00552-w
pmid:34551818
pmcid:PMC8459562
fatcat:xjqvs4b6fbbcjbsznktkwajho4