Traditional bulk sequencing methods are limited to measuring the average signal in a group
of cells, potentially masking heterogeneity, and rare populations. The single-cell resolution …

Single-cell 'omics methodology has yielded unprecedented insights based largely on data-
centric informatics for reducing, and thus interpreting, massive datasets. In parallel …

Across biological systems, cells undergo coordinated changes in gene expression, resulting
in transcriptome dynamics that unfold within a low-dimensional manifold. While low …

Single-cell transcriptomics technologies can uncover changes in the molecular states that
underlie cellular phenotypes. However, understanding the dynamic cellular processes …

Despite the continued efforts, a batch-insensitive tool that can both infer and predict the
developmental dynamics using single-cell genomics is lacking. Here, I present scTour, a …

Measurement of single-cell gene expression at different timepoints enables the study of cell
development. However, due to the resource constraints and technical challenges associated …

As the field of single-cell transcriptomics matures, research is shifting focus from
phenomenological descriptions of cellular phenotypes to a mechanistic understanding of the …

We presented an experimental method called FLOUR-seq, which combines BD Rhapsody
and nanopore sequencing to detect the RNA lifecycle (including nascent, mature, and …

RNA velocity is a powerful paradigm that exploits the temporal information contained in
spliced and unspliced RNA counts to infer transcriptional dynamics. Existing velocity models …

Gene expression dynamics provide directional information for trajectory inference from
single-cell RNA sequencing data. Traditional approaches compute RNA velocity using strict …