Identifying drug-target interactions will greatly narrow down the scope of search of candidate
medications, and thus can serve as the vital first step in drug discovery. Considering that in …

Drug-target Interactions (DTIs) prediction plays a central role in drug discovery.
Computational methods in DTIs prediction have gained more attention because carrying out …

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 …

Accurate prediction of drug–target interactions (DTI) is crucial for drug discovery. Recently,
deep learning (DL) models for show promising performance for DTI prediction. However …

Drug-target interaction (DTI) is the basis of drug discovery. However, it is time-consuming
and costly to determine DTIs experimentally. Over the past decade, various computational …

The drug development is generally arduous, costly, and success rates are low. Thus, the
identification of drug-target interactions (DTIs) has become a crucial step in early stages of …

Background The ability to predict the interaction of drugs with target proteins is essential to
research and development of drug. However, the traditional experimental paradigm is costly …

Exploring drug–target interactions by biomedical experiments requires a lot of human,
financial, and material resources. To save time and cost to meet the needs of the present …

Background Identification of novel drug–target interactions (DTIs) is important for drug
discovery. Experimental determination of such DTIs is costly and time consuming, hence it …

In silico drug-target interaction (DTI) prediction is an important and challenging problem in
biomedical research with a huge potential benefit to the pharmaceutical industry and …