Abstract Computational Drug Discovery, which uses computational techniques to facilitate
and improve the drug discovery process, has aroused considerable interests in recent years …

Identifying drug-target interaction (DTI) candidates is crucial for drug repositioning. However,
usually only positive DTIs are deposited in known databases, which challenges …

Background Investigating and understanding drug-drug interactions (DDIs) is important in
improving the effectiveness of clinical care. DDIs can occur when two or more drugs are …

Abstract Background Drug-drug interactions (DDIs) are a major concern in patients'
medication. It's unfeasible to identify all potential DDIs using experimental methods which …

Identifying interactions between drug compounds and target proteins is an important
process in drug discovery. It is time-consuming and expensive to determine interactions …

Motivation Identifying and developing novel therapeutic effects for existing drugs contributes
to reduction of drug development costs. Most of the previous methods focus on integration of …

Drugs, which treat various diseases, are essential for human health. However, developing
new drugs is quite laborious, time-consuming, and expensive. Although investments into …

Motivation Identifying drug–protein interactions (DPIs) is a critical step in drug repositioning,
which allows reuse of approved drugs that may be effective for treating a different disease …

The challenges of modern drug discovery motivate the use of machine learning-based
methods, such as predicting drug-target interactions or novel indications for already …

Motivation Drug repositioning, the identification of new therapeutic uses for existing drugs, is
crucial for accelerating drug discovery and reducing development costs. Some methods rely …