Knowledge-based Data Integration

Knowledge-Based Data Integration is a data integration approach that leverages structured prior knowledge—such as ontologies, biological pathways, or domain-specific rules—to guide and constrain the integration of omics datasets, distinguishing it from data-driven or statistical integration methods by its reliance on curated, external biological knowledge to enhance interpretability and biological relevance.

110

Publications

4.3K

Citations

637

Authors

273

Institutions

Publications per year

2017–2026

30

Authors

637

  1. CM
    Chris Mungall

    Lawrence Berkeley National Laboratory, United States

    4 publications · 154 citations

    4

    h-index

  2. MH
    Melissa Haendel

    Oregon Health & Science University, United States

    3 publications · 149 citations

    3

    h-index

  3. SC
    Seth Carbon

    Lawrence Berkeley National Laboratory, United States

    3 publications · 141 citations

    3

    h-index

  4. VR
    Vida Ravanmehr

    Jackson Laboratory, United States

    3 publications · 141 citations

    3

    h-index

  5. JR
    Justin Reese

    Lawrence Berkeley National Laboratory, United States

    3 publications · 141 citations

    3

    h-index

1–5 of 637

Venues

  1. BMC Bioinformatics

    11 publications · 390 citations

    11

    h-index

  2. Bioinformatics

    8 publications · 763 citations

    8

    h-index

  3. Journal of Biomedical Informatics

    3 publications · 162 citations

    3

    h-index

  4. Methods in molecular biology

    Book series · 3 publications · 153 citations

    3

    h-index

  5. PLoS Computational Biology

    2 publications · 85 citations

    2

    h-index

1–5