Background Drug discovery is a complex and expensive procedure involving several timely
and costly phases through which new potential pharmaceutical compounds must pass to get …

In recent years, drug repositioning has emerged as a promising alternative to the time-
consuming, expensive and risky process of developing new drugs for diseases. However …

The emergence of neuromorphic computing, inspired by the structure and function of the
human brain, presents a transformative framework for modelling neurological disorders in …

Enhancers are a class of noncoding DNA, serving as crucial regulatory elements in
governing gene expression by binding to transcription factors. The identification of …

Identification of interactions between chemical compounds and proteins is crucial for various
applications, including drug discovery, target identification, network pharmacology, and …

Existing deep learning methods have shown outstanding performance in predicting drug–
target interactions. However, they still have limitations:(1) the over-reliance on locally …

MicroRNAs (miRNAs), vital regulators of gene expression and human health, are intimately
associated with diseases upon dysregulation. Small molecules have emerged as promising …

Background: Drug-Protein Interaction (DPI) identification is crucial in drug discovery. The
high dimensionality of drug and protein features poses challenges for accurate interaction …

As machine learning (ML) becomes increasingly integrated into the drug development
process, accurately predicting Drug-Target Interactions (DTI) becomes a necessity for …

Drug discovery is a time-consuming and costly process that notoriously suffers from low
success rates. Increased availability of chemically relevant data and advances in machine …