Single-cell omics technologies are currently solving biological and medical problems that
earlier have remained elusive, such as discovery of new cell types, cellular differentiation …

Transcription factors (TFs) are essential players in orchestrating the regulatory landscape in
cells. Still, their exact modes of action and dependencies on other regulatory aspects remain …

Inferring the driving regulatory programs from comparative analysis of gene expression data
is a cornerstone of systems biology. Many computational frameworks were developed to …

Transcriptomic signatures based on cellular mRNA expression profiles can be used to
categorize cell types and states. Yet whether different functional groups of genes perform …

Predicting the transcription factor binding site (TFBS) in the whole genome range is
essential in exploring the rule of gene transcription control. Although many deep learning …

Motivation Identifying regulatory regions in the genome is of great interest for understanding
the epigenomic landscape in cells. One fundamental challenge in this context is to find the …

Neuroblastoma (NBL) is a pediatric cancer responsible for more than 15% of cancer deaths
in children, with 800 new cases each year in the United States alone. Genomic amplification …

Inferring gene regulatory networks from single-cell RNA-sequencing trajectories has been
an active area of research yet methods are still needed to identify regulators governing cell …

Alzheimer's disease (AD) is a pervasive neurodegenerative disorder that leads to memory
and behavior impairment severe enough to interfere with daily life activities. Understanding …

Inferring the driving regulatory programs from comparative analysis of gene expression data
is a cornerstone of systems biology. Many computational frameworks were developed to …