This review provides the feasible literature on drug discovery through ML tools and
techniques that are enforced in every phase of drug development to accelerate the research …

The discovery and advances of medicines may be considered as the ultimate relevant
translational science effort that adds to human invulnerability and happiness. But advancing …

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 …

Deep learning (DL), a new generation of artificial neural network research, has transformed
industries, daily lives, and various scientific disciplines in recent years. DL represents …

Advances in biological and medical technologies have been providing us explosive
volumes of biological and physiological data, such as medical images …

In the era of big data, transformation of biomedical big data into valuable knowledge has
been one of the most important challenges in bioinformatics. Deep learning has advanced …

State-of-the-art deep neural networks have achieved impressive results on many image
classification tasks. However, these same architectures have been shown to be unstable to …

Increases in throughput and installed base of biomedical research equipment led to a
massive accumulation of-omics data known to be highly variable, high-dimensional, and …

Motivation Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides
(AMPs), natural components of innate immunity, are popular targets for developing new …

Technological advances in genomics and imaging have led to an explosion of molecular
and cellular profiling data from large numbers of samples. This rapid increase in biological …