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

Single-cell RNA sequencing studies of differentiating systems have raised fundamental
questions regarding the discrete versus continuous nature of both differentiation and cell …

Cellular differentiation is a common underlying feature of all multicellular organisms through
which naïve cells progressively become fate restricted and develop into mature cells with …

Computational trajectory inference enables the reconstruction of cell state dynamics from
single-cell RNA sequencing experiments. However, trajectory inference requires that the …

Advances in single-cell RNA sequencing over the past decade has shifted the discussion of
cell identity toward the transcriptional state of the cell. While the incredible resolution …

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage
differentiation trajectories, along with the characterization of cellular heterogeneity and state …

Despite recent advances in inferring cellular dynamics using single-cell RNA-seq data,
existing trajectory inference (TI) methods face difficulty in accurately reconstructing the cell …

Existing computational methods that use single-cell RNA-sequencing for cell fate prediction
either summarize observations of cell states and their couplings without modeling the …

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular
differentiation trajectories. However, inferring both the state and direction of differentiation is …