Recent experimental developments in genome-wide RNA quantification hold considerable
promise for systems biology. However, rigorously probing the biology of living cells requires …

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

Dimensionality reduction is standard practice for filtering noise and identifying relevant
features in large-scale data analyses. In biology, single-cell genomics studies typically begin …

Gene expression in mammalian cells is highly variable and episodic, resulting in a series of
discontinuous bursts of mRNAs. A challenge is to understand how static promoter …

Metabarcoding is a powerful molecular tool for simultaneously surveying hundreds to
thousands of species from a single sample, underpinning microbiome and environmental …

The snapshot distribution of mRNA counts per cell can be measured using single-molecule
fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are …

The term “RNA-seq” refers to a collection of assays based on sequencing experiments that
involve quantifying RNA species from bulk tissue, from single cells, or from single nuclei …

The serial nature of reactions involved in the RNA life-cycle motivates the incorporation of
delays in models of transcriptional dynamics. The models couple a transcriptional process to …

We present the Python package Monod for the analysis of single-cell RNA sequencing count
data through chemical master equation models. Monod can effectively identify biological …

We motivate and present biVI, which combines the variational autoencoder framework of
scVI with biophysically motivated, bivariate models for nascent and mature RNA …