QSAR. Despite this long tradition, machine learning methods gained substantial momentum
recently triggered by the success of deep learning in many application areas. 1 A wide …

Currently, machine learning methods drive the success of artificial intelligence in academia
and industry. Among machine learning methods, Deep Learning has emerged as a game …

Background Drug discovery processes, such as new drug development, drug synergy, and
drug repurposing, consume significant yearly resources. Computer-aided drug discovery …

Deep learning (DL) algorithms are a subset of machine learning algorithms with the aim of
modeling complex mapping between a set of elements and their classes. In parallel to the …

Highlights•Deep learning technology has gained remarkable success.•We highlight the
recent applications of deep learning in drug discovery research.•Some popular deep …

Over the past decade we have witnessed the increasing sophistication of machine learning
algorithms applied in daily use from internet searches, voice recognition, social network …

Highlights•Six commonly used machine learning methods in QSAR models are
summarized.•Newly developed combinatorial QSAR and hybrid QSAR methods are …

Artificial intelligence (AI) development imitates the workings of the human brain to
comprehend modern problems. The traditional approaches such as high throughput …

Highlights•We review machine learning methods/tools relevant to ligand-based virtual
screening.•Machine learning methods classify compounds and predict new active …

With the development of computer-assisted techniques, research communities, including
biochemistry and deep learning, have been devoted into the drug discovery field for over a …