Artificial intelligence (AI) models based on deep learning now represent the state of the art
for making functional predictions in genomics research. However, the underlying basis on …

Deep Learning (DL) has recently enabled unprecedented advances in one of the grand
challenges in computational biology: the half-century-old problem of protein structure …

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 …

We present a novel class incremental learning approach based on deep neural networks,
which continually learns new tasks with limited memory for storing examples in the previous …

Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …

Identifying and characterizing vascular plants in time and space is required in various
disciplines, eg in forestry, conservation and agriculture. Remote sensing emerged as a key …

The COVID-19 pandemic has emphasized the need for novel drug discovery process.
However, the journey from conceptualizing a drug to its eventual implementation in clinical …

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 …

A few years ago, the first CNN surpassed human performance on ImageNet. However, it
soon became clear that machines lack robustness on more challenging test cases, a major …

In the context of science, the well-known adage" a picture is worth a thousand words" might
well be" a model is worth a thousand datasets." In this manuscript we introduce the SciML …