Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs
and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an …

Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …

The COVID-19 pandemic caused by SARS-CoV-2 is an unprecedentedly significant health
threat, prompting the need for rapidly developing antiviral drugs for the treatment. Drug …

Motivation The use of drug combinations, termed polypharmacy, is common to treat patients
with complex diseases or co-existing conditions. However, a major consequence of …

New technologies have enabled the investigation of biology and human health at an
unprecedented scale and in multiple dimensions. These dimensions include a myriad of …

Currently, there are about 7000 identified rare diseases, together affecting 10% of the
population. However, fewer than 6% of all rare diseases have an approved treatment option …

Identifying new indications for drugs plays an essential role at many phases of drug
research and development. Computational methods are regarded as an effective way to …

Drug repurposing involves the identification of new applications for existing drugs at a lower
cost and in a shorter time. There are different computational drug-repurposing strategies and …

In silico reuse of old drugs (also known as drug repositioning) to treat common and rare
diseases is increasingly becoming an attractive proposition because it involves the use of de …

Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy
highly depends on the reliability of scoring functions (SFs). With the rapid development of …