The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has
advanced our understanding of the pathogenesis of disease and provided valuable insights …

Heterogeneity describes the differences among cancer cells within and between tumors. It
refers to cancer cells describing variations in morphology, transcriptional profiles …

Metabolism is a major regulator of immune cell function, but it remains difficult to study the
metabolic status of individual cells. Here, we present Compass, an algorithm to characterize …

A common drawback of metabolic analyses of complex biological samples is the inability to
consider cell-to-cell heterogeneity in the context of an organ or tissue. To overcome this …

Omic data analysis is steadily growing as a driver of basic and applied molecular biology
research. Core to the interpretation of complex and heterogeneous biological phenotypes …

The metabolic heterogeneity and metabolic interplay between cells are known as significant
contributors to disease treatment resistance. However, with the lack of a mature high …

Organismal aging exhibits wide-ranging hallmarks in divergent cell types across tissues,
organs, and systems. The advancement of single-cell technologies and generation of rich …

Single-cell analysis provides insights into cellular heterogeneity and dynamics of individual
cells. This Feature highlights recent developments in key analytical techniques suited for …

Background Single-cell metabolic studies bring new insights into cellular function, which can
often not be captured on other omics layers. Metabolic information has wide applicability …

Motivation The advancements of single-cell sequencing methods have paved the way for
the characterization of cellular states at unprecedented resolution, revolutionizing the …