Cell State Deconvolution

Cell State Deconvolution is a computational method in single-cell genomics that resolves the dynamic, functional states of cells within heterogeneous tissue samples by disentangling transcriptional profiles from bulk omics data, distinguishing itself from broader cell-type deconvolution by focusing on transient, context-specific cellular phenotypes rather than stable lineage-based classifications.

40

Publications

3.2K

Citations

290

Authors

130

Institutions

Publications per year

2017–2026

35

Authors

290

  1. LA
    Loyal A. Goff

    Johns Hopkins University, United States

    3 publications · 214 citations

    3

    h-index

  2. RS
    Rachel Sealfon

    Princeton University, United States

    3 publications · 214 citations

    3

    h-index

  3. AM
    Annette M. Molinaro

    University of California, San Francisco, United States

    3 publications · 319 citations

    3

    h-index

  4. QH
    Qiwen Hu

    Harvard University, United States

    3 publications · 214 citations

    3

    h-index

  5. JK
    John K. Wiencke

    University of California, San Francisco, United States

    3 publications · 319 citations

    3

    h-index

1–5 of 290

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 6 publications · 108 citations

    6

    h-index

  2. Nature Communications

    6 publications · 655 citations

    6

    h-index

  3. Cell Systems

    2 publications · 196 citations

    2

    h-index

  4. Cell Reports

    2 publications · 674 citations

    2

    h-index

  5. Annals of the Rheumatic Diseases

    ARD · 1 publications · 73 citations

    1

    h-index

1–5