Inferring small molecule-miRNA associations (MMAs) is crucial for revealing the intricacies
of biological processes and disease mechanisms. Deep learning, renowned for its …

Background DNA methylation, instrumental in numerous life processes, underscores the
paramount importance of its accurate prediction. Recent studies suggest that deep learning …

MicroRNAs (miRNAs) are found ubiquitously in biological cells and play a pivotal role in
regulating the expression of numerous target genes. Therapies centered around miRNAs …

Discovering new drugs is a complicated, time-consuming, costly, risky and failure-prone
process. However, about 80% of the drugs that have been approved so far are targeted at …

The time-consuming and expensive nature of traditional drug discovery necessitates a cost-
effective approach to facilitate disease treatment. Drug repositioning, discovering innovative …

Motivation Accurately predicting the degradation capabilities of proteolysis-targeting
chimeras (PROTACs) for given target proteins and E3 ligases is important for PROTAC …

Drug–food interactions (DFIs) crucially impact patient safety and drug efficacy by modifying
absorption, distribution, metabolism, and excretion. The application of deep learning for …

Drug sensitivity significantly influences therapeutic outcomes. Recent discoveries have
highlighted the pivotal role of miRNAs in regulating drug sensitivity by modulating genes …

Personalized cancer drug treatment is emerging as a frontier issue in modern medical
research. Considering the genomic differences among cancer patients, determining the …

Existing studies indicate that dysregulation or abnormal expression of small nucleolar RNA
(snoRNA) is closely associated with various diseases, including lung cancer. Furthermore …