Subnetwork Enrichment Analysis
Subnetwork Enrichment Analysis is a computational method in network-based biomarker discovery that identifies biologically meaningful subnetworks within a larger molecular interaction network by assessing the statistical overrepresentation of functionally related gene or protein sets, thereby distinguishing itself from broader network analysis techniques through its focused evaluation of localized topological and functional enrichment.
113
Publications
7.9K
Citations
681
Authors
265
Institutions
Publications per year
2017–2026
45
113
Discovering regulatory and signalling circuits in molecular interaction networks
Trey Ideker, Owen Ozier, Benno Schwikowski et al. · Bioinformatics · 2002 · 1.2K citations
A Markov random field model for network-based analysis of genomic data
Zhi Wei, Hongzhe Li · Bioinformatics · 2007 · 257 citations · Full text
1–5 of 113
681
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3
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3
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The University of Texas Health Science Center at Houston, United States
3 publications · 360 citations
3
h-index
2
h-index
1–5 of 681
265

Imperial College London
London, United Kingdom
6 h-index
15 publications
614 citations

Icahn School of Medicine at Mount Sinai
New York, United States
5 h-index
53 publications
4.4K citations
University of Florida
Gainesville, United States
4 h-index
10 publications
537 citations
Harvard University
Cambridge, United States
4 h-index
9 publications
851 citations
Acıbadem Adana Hospital
Adana, Turkey
3 h-index
6 publications
1.1K citations

Shanghai Jiao Tong University
Shanghai, China
3 h-index
16 publications
499 citations
Dana-Farber Cancer Institute
Boston, United States
3 h-index
6 publications
612 citations
Université Paris Cité
Paris, France
3 h-index
18 publications
432 citations
1–8 of 265
21 publications · 3K citations
18
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9 publications · 439 citations
9
h-index
6 publications · 340 citations
6
h-index
4 publications · 126 citations
4
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4 publications · 304 citations
4
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