In the dynamic field of drug discovery, deep attention neural networks are revolutionizing our
approach to complex data. This review explores the attention mechanism and its extended …

Recently, attention mechanism and derived models have gained significant traction in drug
development due to their outstanding performance and interpretability in handling complex …

The prediction of interactions between novel drugs and biological targets is a vital step in the
early stage of the drug discovery pipeline. Many deep learning approaches have been …

The interactions between therapeutics and their targets are an important part of the drug
development process. To counter the cost, time and accuracy related issues, novel and …

In the wake of the novel Covid-19 disease pandemic, the global economy has been affected
and health crises are widespread. The disease is still incurable, and no effective treatment …

The end-to-end process in the discovery of drugs involves therapeutic candidate
identification, validation of identified targets, identification of hit compound series, lead …