Multimodal, single-cell genomics technologies enable simultaneous measurement of
multiple facets of DNA and RNA processing in the cell. This creates opportunities for …

The trillions of cells in our bodies exhibit diverse characteristics, expressing various
transcripts and engaging in different biological functions. Detecting and categorizing these …

Single-cell RNA sequencing methods have led to improved understanding of the
heterogeneity and transcriptomic states present in complex biological systems. Recently, the …

Single-cell genomics has now made it possible to create a comprehensive atlas of human
cells. At the same time, it has reopened definitions of a cell's identity and of the ways in …

The abundance of new computational methods for processing and interpreting
transcriptomes at a single cell level raises the need for in silico platforms for evaluation and …

Highlights•Single-cell temporal transcriptomics expedites the study of cellular dynamics.•The
dynamics of a cell is inferred from the collective states of observed cells.•The inferred …

Single-cell transcriptomics experiments provide gene expression snapshots of
heterogeneous cell populations across cell states. These snapshots have been used to infer …

Highlights•Single cell sequencing,(imaging) mass cytometry, time-lapse imaging.•Stochastic
reaction model, probabilistic graphical model, in-/extrinsic variability.•Ab initio cell type …

Single-cell genomics has recently emerged as a powerful tool for observing multicellular
systems at a much higher level of resolution and depth than previously possible. High …

Cell differentiation processes are achieved through a continuum of hierarchical intermediate
cell states that might be captured by single-cell RNA seq. Existing computational …