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 …

Genome-wide expression profiling of gene transcripts has been successfully applied in
biomedical discovery for over a decade. Based on the premises of this technology …

Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming
and costly to determine DTI experimentally. Hence, it is necessary to develop computational …

Drug repositioning helps fully explore indications for marketed drugs and clinical
candidates. Here we show that the clinical side-effects (SEs) provide a human phenotypic …

The need and opportunity to discover therapeutics for rare or orphan diseases are
enormous. Due to limited prevalence and/or commercial potential, of the approximately …

Identifying potential protein targets for a small-compound ligand query is crucial to the
process of drug development. However, there are tens of thousands of proteins in human …

Covering: up to 2014 In silico approaches have been widely recognised to be useful for drug
discovery. Here, we consider the significance of available databases of medicinal plants and …

Identifying new indications for existing drugs (drug repositioning) is an efficient way of
maximizing their potential. Adverse drug reaction (ADR) is one of the leading causes of …

The rapidly increasing amount of public data in chemistry and biology provides new
opportunities for large-scale data mining for drug discovery. Systematic integration of these …

Prediction of the drug–target affinity (DTA) plays an important role in drug discovery. Existing
deep learning methods for DTA prediction typically leverage a single modality, namely …