Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to
quantify the gene expression profile of thousands of single cells simultaneously. Analysis of …

Generative pretrained models have achieved remarkable success in various domains such
as language and computer vision. Specifically, the combination of large-scale diverse …

High-throughput single-cell profiling provides an unprecedented ability to uncover the
molecular states of millions of cells. These technologies are, however, destructive to cells …

Single-cell omics technologies have revolutionized the study of gene regulation in complex
tissues. A major computational challenge in analyzing these datasets is to project the large …

Aging, often considered a result of random cellular damage, can be accurately estimated
using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we …

The increasing generation of population-level single-cell atlases has the potential to link
sample metadata with cellular data. Constructing such references requires integration of …

Aging is often perceived as a degenerative process resulting from random accrual of cellular
damage over time. Despite this, age can be accurately estimated by epigenetic clocks based …

Current biotechnologies can simultaneously measure multiple high-dimensional modalities
(eg, RNA, DNA accessibility, and protein) from the same cells. A combination of different …

Biology has become a data-intensive science. Recent technological advances in single-cell
genomics have enabled the measurement of multiple facets of cellular state, producing …

Background Single-cell RNA-sequencing (scRNA-seq) measures gene expression in single
cells, while single-nucleus ATAC-sequencing (snATAC-seq) quantifies chromatin …