Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …

Computational drug repurposing aims to identify new indications for existing drugs by
utilizing high-throughput data, often in the form of biomedical knowledge graphs. However …

Graph machine learning (GML) is receiving growing interest within the pharmaceutical and
biotechnology industries for its ability to model biomolecular structures, the functional …

Drug development is time‐consuming and expensive. Repurposing existing drugs for new
therapies is an attractive solution that accelerates drug development at reduced …

Develo** new drugs remains prohibitively expensive, time-consuming, and often involves
safety issues. Accurate prediction of drug-target interactions (DTIs) can guide the drug …

Drug repositioning is a promising drug development technique to identify new indications for
existing drugs. However, existing computational models only make use of lower-order …

Artificial intelligence (AI) is revolutionizing the current process of drug design and
development, addressing the challenges encountered in its various stages. By utilizing AI …

Motivation There are various interaction/association bipartite networks in biomolecular
systems. Identifying unobserved links in biomedical bipartite networks helps to understand …

Graph neural networks are essential in mining complex relationships in graphs. However,
most methods ignore the global location information of nodes and the discrepancy between …