Pseudotime Ordering Algorithms

Pseudotime Ordering Algorithms is a computational methodology that infers the temporal progression of cells in a biological process by constructing a latent ordering from high-dimensional single-cell data based on transcriptional similarity, thereby enabling the reconstruction of dynamic trajectories in the absence of explicit time measurements.

8

Publications

1.2K

Citations

21

Authors

14

Institutions

Publications per year

2017–2026

4

Variants

Pseudotime Inference Algorithms

Authors

21

  1. KR
    Kieran R. Campbell

    University of Oxford, United Kingdom

    2 publications · 70 citations

    2

    h-index

  2. OJ
    Owen J. L. Rackham

    Duke-NUS Medical School, Singapore

    1 publications · 130 citations

    1

    h-index

  3. CY
    Christopher Yau

    University of Oxford, United Kingdom

    1 publications · 22 citations

    1

    h-index

  4. CW
    Caleb Webber

    University of Oxford, United Kingdom

    1 publications · 48 citations

    1

    h-index

  5. HJ
    Hongkai Ji

    Johns Hopkins University, United States

    1 publications · 716 citations

    1

    h-index

1–5 of 21

Venues

  1. Bioinformatics

    5 publications · 422 citations

    5

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 70 citations

    2

    h-index

  3. Nucleic Acids Research

    1 publications · 716 citations

    1

    h-index

1–3