Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …

Genetic variant calling from DNA sequencing has enabled understanding of germline
variation in hundreds of thousands of humans. Sequencing technologies and variant-calling …

Abstract JASPAR (https://jaspar. elixir. no/) is a widely-used open-access database
presenting manually curated high-quality and non-redundant DNA-binding profiles for …

Recent advances in machine learning have enabled the development of next-generation
predictive models for complex computational biology problems, thereby spurring the use of …

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality
worldwide. Its complexity is influenced by various signal transduction networks that govern …

Artificial intelligence (AI) has transformed pharmacological research through machine
learning, deep learning, and natural language processing. These advancements have …

Inferring gene regulatory networks (GRNs) is a fundamental challenge in biology that aims
to unravel the complex relationships between genes and their regulators. Deciphering these …

The integration of artificial intelligence technologies has propelled the progress of clinical
and genomic medicine in recent years. The significant increase in computing power has …

In the rapidly evolving landscape of genomics, deep learning has emerged as a useful tool
for tackling complex computational challenges. This review focuses on the transformative …

In population genetics, the emergence of large-scale genomic data for various species and
populations has provided new opportunities to understand the evolutionary forces that drive …