Regression-based Deconvolution
Regression-Based Deconvolution is a computational method in cell-type deconvolution that employs regression models to estimate the proportional contributions of distinct cell types within a bulk tissue sample by leveraging gene expression signatures as predictors.
18
Publications
528
Citations
79
Authors
36
Institutions
Publications per year
2017–2026
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University of Pittsburgh
Pittsburgh, United States
2 h-index
6 publications
218 citations

Pomeranian Medical University
Szczecin, Poland
1 h-index
1 publications
21 citations
State Key Laboratory of Digital Medical Engineering
Nanjing, China
1 h-index
4 publications
96 citations

Université Lille Nord de France
Lille, France
1 h-index
1 publications
22 citations
Sandia National Laboratories
Albuquerque, United States
1 h-index
1 publications
109 citations
Université de Lille
Lille, France
1 h-index
1 publications
22 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
2 publications
46 citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
1 h-index
1 publications
25 citations
1–8 of 36
GW · 2 publications · 151 citations
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1 publications · 23 citations
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1 publications · 23 citations
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1 publications · 22 citations
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1 publications · 43 citations
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