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

Authors

681

  1. OU
    Osman Uğur Sezerman

    Sabancı Üniversitesi, Türkiye

    3 publications · 570 citations

    3

    h-index

  2. EÜ
    Ege Ülgen

    Kent Hastanesi, Türkiye

    3 publications · 570 citations

    3

    h-index

  3. BJ
    Benjamin J. Raphael

    Princeton University, United States

    3 publications · 718 citations

    3

    h-index

  4. ZZ
    Zhongming Zhao

    The University of Texas Health Science Center at Houston, United States

    3 publications · 360 citations

    3

    h-index

  5. RZ
    Ralf Zimmer

    Ludwig-Maximilians-Universität München, Germany

    2 publications · 31 citations

    2

    h-index

1–5 of 681

Venues

  1. Bioinformatics

    21 publications · 3K citations

    18

    h-index

  2. BMC Bioinformatics

    9 publications · 439 citations

    9

    h-index

  3. PLoS ONE

    6 publications · 340 citations

    6

    h-index

  4. Scientific Reports

    4 publications · 126 citations

    4

    h-index

  5. PLoS Computational Biology

    4 publications · 304 citations

    4

    h-index

1–5