Histone mark age of human tissues and cell types.

Aging is a complex and multifaceted process involving many epigenetic alterations. One key area of interest in aging research is the role of histone modifications, which can dynamically regulate gene expression. Here, we conducted a pan-tissue analysis of the dynamics of seven key histone modifications during human aging.

Hallmarks of aging: A user's guide for comparative biologists.

Since the first description of a set of characteristics of aging as so-called hallmarks or pillars in 2013/2014, these characteristics have served as guideposts for the research in aging biology. They have been examined in a range of contexts, across tissues, in response to disease conditions or environmental factors, and served as a benchmark for various anti-aging interventions. While the hallmarks of aging were intended to capture generalizable characteristics of aging, they are derived mostly from studies of rodents and humans.

BindCompare: a novel integrated protein-nucleic acid binding analysis platform.

Summary: Advanced genomic technologies have generated thousands of protein-nucleic acid binding datasets that have the potential to identify testable gene regulatory network (GRNs) models governed by combinatorial associations between factors. Transcription factors (TFs), and RNA binding proteins (RBPs) are nucleic-acid binding proteins regulating gene expression and are key drivers of GRN function. However, the combinatorial mechanisms by which the interactions between specific TFs and RBPs regulate gene expression remain largely unknown.

Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation.

Inferring gene regulatory networks from gene expression data is an important and challenging problem in the biology community. We propose OTVelo, a methodology that takes time-stamped single-cell gene expression data as input and predicts gene regulation across two time points. It is known that the rate of change of gene expression, which we will refer to as gene velocity, provides crucial information that enhances such inference; however, this information is not always available due to the limitations in sequencing depth.