Epigenomic Data Integration

Epigenomic Data Integration is a computational and statistical methodology that synthesizes diverse epigenomic datasets across multiple biological contexts, technologies, or temporal states to infer coherent regulatory patterns, distinguishing itself from general data integration by its specific focus on the genome-wide chemical and structural modifications of chromatin that modulate gene expression without altering DNA sequence.

208

Publications

27.8K

Citations

1.5K

Authors

471

Institutions

Publications per year

2017–2026

131

Authors

1.5K

  1. YB
    Yīmíng Bào

    Beijing Institute of Genomics, China

    5 publications · 600 citations

    5

    h-index

  2. RL
    Rujiao Li

    Beijing Institute of Genomics, China

    5 publications · 600 citations

    5

    h-index

  3. TW
    Ting Wang

    Washington University in St. Louis, United States

    5 publications · 564 citations

    5

    h-index

  4. RC
    Ross C. Hardison

    Pennsylvania State University, United States

    4 publications · 267 citations

    4

    h-index

  5. DZ
    Dong Zou

    Beijing Institute of Genomics, China

    4 publications · 572 citations

    4

    h-index

1–5 of 1.5K

Venues

  1. Nucleic Acids Research

    38 publications · 9.8K citations

    29

    h-index

  2. Bioinformatics

    22 publications · 1.9K citations

    17

    h-index

  3. Genome biology

    16 publications · 1.2K citations

    14

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 9 publications · 244 citations

    9

    h-index

  5. BMC Bioinformatics

    8 publications · 451 citations

    8

    h-index

1–5