Reference-based Deconvolution

Reference-Based Deconvolution is a computational approach in cell-type deconvolution that belongs to the class of methods requiring prior knowledge of cell-type-specific gene expression profiles, distinguished by its reliance on a pre-defined reference signature matrix to estimate the proportional contributions of distinct cell types within bulk tissue samples.

39

Publications

3.3K

Citations

159

Authors

99

Institutions

Publications per year

2017–2026

27

Authors

159

  1. GA
    Gareth A. Morris

    University of Manchester, United Kingdom

    8 publications · 291 citations

    8

    h-index

  2. KT
    Karl T. Kelsey

    Brown University, United States

    5 publications · 1K citations

    5

    h-index

  3. LA
    Lucas A. Salas

    Dartmouth College, United States

    5 publications · 1K citations

    5

    h-index

  4. DC
    Devin C. Koestler

    University of Kansas Medical Center, United States

    5 publications · 1K citations

    5

    h-index

  5. BC
    Brock C. Christensen

    Dartmouth College, United States

    5 publications · 1K citations

    5

    h-index

1–5 of 159

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 6 publications · 132 citations

    6

    h-index

  2. Magnetic Resonance in Chemistry

    MRC · 5 publications · 183 citations

    5

    h-index

  3. Nature Communications

    4 publications · 909 citations

    4

    h-index

  4. Briefings in Bioinformatics

    3 publications · 123 citations

    3

    h-index

  5. Journal of Magnetic Resonance

    JMR · 3 publications · 102 citations

    3

    h-index

1–5