Kernel-based Network Inference
Kernel-Based Network Inference is a computational method within regulatory network inference that employs kernel functions to model nonlinear dependencies among biological entities, distinguishing itself by leveraging reproducing kernel Hilbert spaces to infer regulatory interactions from high-dimensional genomics data.
24
Publications
1.1K
Citations
76
Authors
48
Institutions
Publications per year
2017–2026
8
Parents
24
Network inference with Granger causality ensembles on single-cell transcriptomics
Atul Deshpande, Li‐Fang Chu, Ron Stewart et al. · Cell Reports · 2022 · 125 citations · Full text
Yan Qi, Yasir Suhail, Yu-Yi Lin et al. · Genome Research · 2008 · 98 citations · Full text
1–5 of 24
76
Informatique, BioInformatique, Systèmes Complexes, France
3 publications · 120 citations
3
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2
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2
h-index
École Nationale Supérieure des Mines de Paris, France
2 publications · 241 citations
2
h-index
1
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1–5 of 76
48

Institut Curie
Paris, France
3 h-index
6 publications
138 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
9 publications
275 citations
Informatique, BioInformatique, Systèmes Complexes
Évry-Courcouronnes, France
3 h-index
7 publications
277 citations

École Nationale Supérieure des Mines de Paris
Paris, France
2 h-index
3 publications
256 citations
Max Planck Institute for Biological Cybernetics
Tübingen, Germany
2 h-index
3 publications
135 citations
Max Planck Society
Munich, Germany
2 h-index
3 publications
135 citations
University of Liège
Liège, Belgium
2 h-index
3 publications
125 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
2 publications
34 citations
1–8 of 48
3 publications · 355 citations
3
h-index
3 publications · 112 citations
3
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1 publications · 30 citations
1
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1 publications · 23 citations
1
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1 publications · 17 citations
1
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1–5