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 …

Single-cell technologies have transformed our understanding of human tissues. Yet, studies
typically capture only a limited number of donors and disagree on cell type definitions …

Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over
the past decade, particularly in developmental biology, cancer, immunology, and …

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

The interplay between chromatin, transcription factors and genes generates complex
regulatory circuits that can be represented as gene regulatory networks (GRNs). The study …

Mapping single-cell sequencing profiles to comprehensive reference datasets provides a
powerful alternative to unsupervised analysis. However, most reference datasets are …

Improved scale, multiplexing and resolution are establishing spatial nucleic acid and protein
profiling methods as a major pillar for cellular atlas building of complex samples, from …

The mammalian brain consists of millions to billions of cells that are organized into many cell
types with specific spatial distribution patterns and structural and functional properties …

It has been 15 years since the advent of the genome-wide association study (GWAS) era.
Here, we review how this experimental design has realized its promise by facilitating an …