The expanding scale and inherent complexity of biological data have encouraged a growing
use of machine learning in biology to build informative and predictive models of the …

Deep learning methods are a class of machine learning techniques capable of identifying
highly complex patterns in large datasets. Here, we provide a perspective and primer on …

N 6-Methyladenosine (m6A) refers to methylation modification of the adenosine nucleotide
acid at the nitrogen-6 position. Many conventional computational methods for identifying N 6 …

The human gene catalogue is essentially complete, but we lack an equivalently vetted
inventory of bona fide human enhancers. Hundreds of thousands of candidate enhancers …

Recent progress in whole-genome mapping and imaging technologies has enabled the
characterization of the spatial organization and folding of the genome in the nucleus. In …

The transformer-based language models, including vanilla transformer, BERT and GPT-3,
have achieved revolutionary breakthroughs in the field of natural language processing …

Genomics is advancing towards data-driven science. Through the advent of high-throughput
data generating technologies in human genomics, we are overwhelmed with the heap of …

Genome-wide association studies (GWAS) have revealed thousands of genetic loci that
underpin the complex biology of many human traits. However, the strength of GWAS–the …

Revealing the function of uncharacterized genes is a fundamental challenge in an era of
ever-increasing volumes of sequencing data. Here, we present a concept for tackling this …

Abstract Machine learning methods have been widely applied to big data analysis in
genomics and epigenomics research. Although accuracy and efficiency are common goals …