Drug–drug interactions (DDIs) are known as the main cause of life-threatening adverse
events, and their identification is a key task in drug development. Existing computational …

The prediction of drug-target interactions (DTIs) is a critical phase in the sustainable drug
development process, especially when the research focus is to capitalize on the …

The lengthy and expensive process of developing new drugs from scratch, coupled with a
high failure rate, has prompted the emergence of drug repurposing/repositioning as a more …

Drug discovery is the process of new drug identification. This process is driven by the
increasing data from existing chemical libraries and data banks. The knowledge graph is …

Drug repositioning is a faster and more affordable solution than traditional drug discovery
approaches. From this perspective, computational drug repositioning using knowledge …

The field of drug discovery has entered a plateau stage lately. It is increasingly more
expensive and time-demanding to introduce new drugs into the market. One of the main …

Knowledge graph (KG) is used to represent data in terms of entities and structural relations
between the entities. This representation can be used to solve complex problems such as …

Drug repositioning, which recommends approved drugs to potential targets by predicting
drug-target interactions (DTIs), can save the cost and shorten the period of drug …

Prediction of Drug-target interaction (DTI) is an important topic in bioinformatics which plays
an important role in the process of drug discovery. Although many machine learning …

Drug repurposing is a technique for probing new usages of existing medicines, but its
traditional methods, such as computational approaches, can be time-consuming and …