Super-enhancer Networks

Super-Enhancer Networks is a computational framework that integrates genomewide epigenetic and transcriptional data to model large clusters of enhancers with exceptionally high regulatory activity, distinguishing it from general enhancer network models by prioritizing cell-identity-associated genes through coordinated, high-intensity transcriptional control.

78

Publications

10K

Citations

989

Authors

374

Institutions

Publications per year

2017–2026

70

Authors

989

  1. RA
    Richard A. Young

    Whitehead Institute for Biomedical Research, United States

    6 publications · 917 citations

    6

    h-index

  2. DL
    De‐Chen Lin

    Cedars-Sinai Medical Center, United States

    6 publications · 381 citations

    6

    h-index

  3. BJ
    Brian J. Abraham

    Whitehead Institute for Biomedical Research, United States

    5 publications · 4.8K citations

    5

    h-index

  4. HW
    Henry W. Long

    Dana-Farber Cancer Institute, United States

    4 publications · 210 citations

    4

    h-index

  5. CR
    Christopher R. Vakoc

    Cold Spring Harbor Laboratory, United States

    3 publications · 377 citations

    3

    h-index

1–5 of 989

Venues

  1. Nature Communications

    9 publications · 660 citations

    9

    h-index

  2. Nucleic Acids Research

    6 publications · 316 citations

    6

    h-index

  3. Cell Reports

    4 publications · 230 citations

    4

    h-index

  4. Oncogene

    3 publications · 151 citations

    3

    h-index

  5. Leukemia

    3 publications · 262 citations

    3

    h-index

1–5