Bayesian Functional Annotation Integration

Bayesian Functional Annotation Integration is a computational framework that integrates diverse genomic data sources into functional annotations of genetic elements through probabilistic modeling based on Bayes' theorem, distinguishing itself by quantifying uncertainty and prior knowledge in the annotation process.

4

Publications

640

Citations

22

Authors

11

Institutions

Publications per year

2017–2026

1

Authors

22

  1. DB
    David Botstein

    Massachusetts Institute of Technology, United States

    1 publications · 535 citations

    1

    h-index

  2. TH
    T. Huizinga

    Leiden University Medical Center, Netherlands

    1 publications · 27 citations

    1

    h-index

  3. OG
    Olga G. Troyanskaya

    Princeton University, United States

    1 publications · 535 citations

    1

    h-index

  4. FY
    Fang Yu

    University of Nebraska Medical Center, United States

    1 publications · 14 citations

    1

    h-index

  5. DW
    David W. Rowe

    UConn Health, United States

    1 publications · 14 citations

    1

    h-index

1–5 of 22

Venues

  1. BMC Proceedings

    1 publications · 27 citations

    1

    h-index

  2. The American Journal of Human Genetics

    AJHG · 1 publications · 64 citations

    1

    h-index

  3. Proceedings of the National Academy of Sciences

    PNAS · 1 publications · 535 citations

    1

    h-index

  4. Statistics in Biosciences

    SIB · 1 publications · 14 citations

    1

    h-index

1–4