Rule-based Annotation

Rule-Based Annotation is a protein function annotation method that assigns functional attributes to proteins through predefined, logic-based rules derived from established biological knowledge, distinguishing it from statistical or machine learning approaches by its reliance on explicit, human-curated inference criteria.

47

Publications

3K

Citations

310

Authors

81

Institutions

Publications per year

2017–2026

11

Authors

310

  1. GY
    Gong-Xin Yu

    Argonne National Laboratory, United States

    2 publications · 28 citations

    2

    h-index

  2. SG
    Sébastien Géhant

    SIB Swiss Institute of Bioinformatics, Switzerland

    2 publications · 89 citations

    2

    h-index

  3. CW
    Cathy Wu

    Georgetown University, United States

    2 publications · 198 citations

    2

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  4. CH
    Chantal Hulo

    SIB Swiss Institute of Bioinformatics, Switzerland

    3 publications · 164 citations

    2

    h-index

  5. MP
    Matthew P. Lungren

    Stanford University, United States

    2 publications · 262 citations

    2

    h-index

1–5 of 310

Venues

  1. Bioinformatics

    6 publications · 330 citations

    6

    h-index

  2. BMC Bioinformatics

    3 publications · 92 citations

    3

    h-index

  3. Nucleic Acids Research

    2 publications · 1K citations

    2

    h-index

  4. Computer applications in the biosciences

    CABIOS · 1 publications · 123 citations

    1

    h-index

  5. 1

    h-index

1–5