Probabilistic Deconvolution

Probabilistic Deconvolution is a computational method within cell-type deconvolution that distinguishes itself by inferring cell type proportions through probabilistic modeling of gene expression data under uncertainty.

31

Publications

1.8K

Citations

150

Authors

75

Institutions

Publications per year

2017–2026

10

Authors

150

  1. AA
    Alessandro Arrigo

    Vita-Salute San Raffaele University, Italy

    2 publications · 144 citations

    2

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  2. AC
    Alessandro Calamuneri

    University of Messina, Italy

    2 publications · 144 citations

    2

    h-index

  3. MG
    Michele Gaeta

    University of Messina, Italy

    2 publications · 144 citations

    2

    h-index

  4. AW
    Andrew W. Robertson

    Columbia University, United States

    2 publications · 179 citations

    2

    h-index

  5. TD
    Timothy D. Johnson

    University of Michigan, United States

    2 publications · 36 citations

    2

    h-index

1–5 of 150

Venues

  1. Biometrics

    2 publications · 36 citations

    2

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  2. Scientific Reports

    2 publications · 43 citations

    2

    h-index

  3. American Journal of Neuroradiology

    AJNR · 2 publications · 122 citations

    2

    h-index

  4. Nuclear Instruments and Methods

    2 publications · 179 citations

    2

    h-index

  5. 1

    h-index

1–5