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

Despite advances in uncovering the mechanisms that underlie neuroinflammation and
neurodegenerative disease, therapies that prevent neuronal loss remain elusive. Targeting …

Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions
using expression similarity or RNA velocity to reconstruct state-change trajectories; however …

Single-cell biology is facing a crisis of sorts. Vast numbers of single-cell molecular profiles
are being generated, clustered and annotated. However, this is overwhelmingly ad hoc, and …

Multi-omic single-cell datasets, in which multiple molecular modalities are profiled within the
same cell, offer an opportunity to understand the temporal relationship between epigenome …

RNA velocity provides an approach for inferring cellular state transitions from single-cell
RNA sequencing (scRNA-seq) data. Conventional RNA velocity models infer universal …

We perform a thorough analysis of RNA velocity methods, with a view towards
understanding the suitability of the various assumptions underlying popular …

We present a multiomic cell atlas of human lung development that combines single-cell RNA
and ATAC sequencing, high-throughput spatial transcriptomics, and single-cell imaging …

RNA velocity has been rapidly adopted to guide interpretation of transcriptional dynamics in
snapshot single-cell data; however, current approaches for estimating RNA velocity lack …

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 …