Cross-study Data Integration

Cross-Study Data Integration is a metagenomic integration approach that synthesizes heterogeneous genomic data across multiple independent studies by harmonizing variable experimental designs, sequencing protocols, and biological contexts to enable comparative and integrative analysis beyond the scope of individual studies.

47

Publications

4.5K

Citations

421

Authors

226

Institutions

Publications per year

2017–2026

22

Authors

421

  1. PR
    Paul R. Burton

    University of Leicester, United Kingdom

    2 publications · 226 citations

    2

    h-index

  2. YK
    Yongsoo Kim

    Pennsylvania State University, United States

    2 publications · 55 citations

    2

    h-index

  3. YW
    Yuan-Ting Wu

    Pennsylvania State University, United States

    2 publications · 55 citations

    2

    h-index

  4. AA
    Ashwin A. Bhandiwad

    University of Washington, United States

    2 publications · 55 citations

    2

    h-index

  5. GC
    George C. Tseng

    University of Pittsburgh, United States

    2 publications · 198 citations

    2

    h-index

1–5 of 421

Venues

  1. Bioinformatics

    4 publications · 156 citations

    4

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 3 publications · 90 citations

    3

    h-index

  3. BMC Bioinformatics

    2 publications · 40 citations

    2

    h-index

  4. NeuroImage

    2 publications · 83 citations

    2

    h-index

  5. Psychological Methods

    2 publications · 1.1K citations

    2

    h-index

1–5