Identifying interactions between known drugs and targets is a major challenge in drug
repositioning. In silico prediction of drug–target interaction (DTI) can speed up the expensive …

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

Background The key to modern drug discovery is to find, identify and prepare drug
molecular targets. However, due to the influence of throughput, precision and cost …

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 …

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 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 …

The identification of drug-target interactions (DTIs) is an important process in drug
repositioning and drug discovery. However, it is very expensive and time-consuming to …

Drug discovery based on artificial intelligence has been in the spotlight recently as it
significantly reduces the time and cost required for developing novel drugs. With the …

Drug–target interaction (DTI) prediction reduces the cost and time of drug development, and
plays a vital role in drug discovery. However, most of research does not fully explore the …

Drug-target interaction (DTI) prediction plays a crucial role in drug repositioning and virtual
drug screening. Most DTI prediction methods cast the problem as a binary classification task …