Single-cell Network Inference
Single-Cell Network Inference is a computational methodology that distinguishes itself by reconstructing gene regulatory or cellular interaction networks from high-dimensional single-cell omics data, enabling the characterization of regulatory dynamics and functional relationships at individual cell resolution.
156
Publications
31.4K
Citations
818
Authors
312
Institutions
Publications per year
2017–2026
138
Parents
156
SCENIC: single-cell regulatory network inference and clustering
Sara Aibar, Carmen Bravo González‐Blas, Thomas Moerman et al. · Nature Methods · 2017 · 6.9K citations · Full text
Recovering Gene Interactions from Single-Cell Data Using Data Diffusion
David van Dijk, Roshan Sharma, Juozas Nainys et al. · Cell · 2018 · 1.9K citations · Full text
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Inserm
Paris, France
8 h-index
29 publications
4.2K citations

Centre National de la Recherche Scientifique
Paris, France
7 h-index
21 publications
1.5K citations
University of Cambridge
Cambridge, United Kingdom
6 h-index
26 publications
4.3K citations
ETH Zurich
Zurich, Switzerland
6 h-index
14 publications
878 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
20 publications
1.6K citations
University of California, Irvine
Irvine, United States
6 h-index
24 publications
1.9K citations

École Normale Supérieure de Lyon
Lyon, France
5 h-index
14 publications
1.1K citations
Shandong University
Jinan, China
5 h-index
19 publications
1.5K citations
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Repository · 22 publications · 828 citations
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15 publications · 1.6K citations
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10 publications · 424 citations
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11 publications · 1.1K citations
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4 publications · 96 citations
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