There are two main ways to discover or design small drug molecules. The first involves fine-
tuning existing molecules or commercially successful drugs through quantitative structure …

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the
pharmaceutical industry, including drug screening, design, and repurposing. However …

Drug synergy prediction plays a vital role in cancer treatment. Because experimental
approaches are labor-intensive and expensive, computational-based approaches get more …

Motivation Screening bioactive compounds in cancer cell lines receive more attention.
Multidisciplinary drugs or drug combinations have a more effective role in treatments and …

Abstract Background The Drug–Target Interaction (DTI) prediction uses a drug molecule and
a protein sequence as inputs to predict the binding affinity value. In recent years, deep …

Background Prediction of drug–target interaction (DTI) is an essential step for drug discovery
and drug reposition. Traditional methods are mostly time-consuming and labor-intensive …

Spatial transcriptomics technologies have shed light on the complexities of tissue structures
by accurately map** spatial microenvironments. Nonetheless, a myriad of methods …

Virtual screening has emerged as a valuable computational tool for predicting compound–
protein interactions, offering a cost-effective and rapid approach to identifying potential …

Prediction of drug–target interactions (DTIs) is essential in medicine field, since it benefits
the identification of molecular structures potentially interacting with drugs and facilitates the …

Recently, deep learning has become the essential methodology for Drug–Target Interaction
(DTI) prediction. However, the existing learning-based representation methods embed the …