Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …

The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome
from single cells is transforming our understanding of cell biology in health and disease. In …

Single-cell multi-omics technologies and methods characterize cell states and activities by
simultaneously integrating various single-modality omics methods that profile the …

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

In the last decade, single-cell RNA sequencing routinely performed on large numbers of
single cells has greatly advanced our understanding of the underlying heterogeneity of …

The recent development of experimental methods for measuring chromatin state at single-
cell resolution has created a need for computational tools capable of analyzing these …

A key aspect of nearly all single-cell sequencing experiments is dissociation of intact tissues
into single-cell suspensions. While many protocols have been optimized for optimal cell …

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods,
together with associated computational tools and the growing availability of public data …

Single-cell atlases promise to provide a 'missing link'between genes, diseases and
therapies. By identifying the specific cell types, states, programs and contexts where disease …

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic
alterations that enable uncontrolled growth and expansion to neighboring and distal tissues …