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

Integrating single-cell multi-omics data is a challenging task that has led to new insights into
complex cellular systems. Various computational methods have been proposed to effectively …

Organoids are three-dimensional structures derived from stem cells that mimic the
organization and function of specific organs, making them valuable tools for studying …

Artificial intelligence (AI) is a powerful approach for solving complex problems in the
processing, analysis, and interpretation of omics data, as well as the integration of multi …

The profiling of multiple molecular layers from the same set of cells has recently become
possible. There is thus a growing need for multi-view learning methods able to jointly …

Recent extensions of single-cell studies to multiple data modalities raise new questions
regarding experimental design. For example, the challenge of sparsity in single-omics data …

Advanced genomics, transcriptomics, and epigenomics techniques are providing
unprecedented insights into the understanding of the molecular underpinnings of the central …

In the context of precision medicine, multiomics data integration provides a comprehensive
understanding of underlying biological processes and is critical for disease diagnosis and …

Highlights•Recent progress in single-cell and spatial technologies.•Applications of single-
cell and spatial technology in biomedical and environmental studies.•Spatial multi-omics …