Benchmarking Binding Affinity Models

Benchmarking Binding Affinity Models is a systematic evaluation framework that, as a subclass of computational model assessment methods, specifically quantifies and compares the predictive accuracy, generalizability, and robustness of binding affinity models using standardized datasets, tasks, and performance metrics within the domain of molecular interaction modeling.

29

Publications

2.6K

Citations

149

Authors

70

Institutions

Publications per year

2017–2026

17

Authors

149

  1. MN
    Morten Nielsen

    Technical University of Denmark, Denmark

    4 publications · 561 citations

    4

    h-index

  2. BP
    Bjoern Peters

    La Jolla Institute for Immunology, United States

    4 publications · 561 citations

    4

    h-index

  3. AS
    Alessandro Sette

    La Jolla Institute for Immunology, United States

    3 publications · 461 citations

    3

    h-index

  4. OL
    Ole Lund

    Technical University of Denmark, Denmark

    3 publications · 461 citations

    3

    h-index

  5. JS
    John Sidney

    La Jolla Institute for Immunology, United States

    3 publications · 461 citations

    3

    h-index

1–5 of 149

Venues

  1. Journal of Chemical Information and Modeling

    JCIM · 4 publications · 326 citations

    4

    h-index

  2. Bioinformatics

    3 publications · 268 citations

    3

    h-index

  3. Protein Science

    PS · 2 publications · 69 citations

    2

    h-index

  4. Briefings in Bioinformatics

    2 publications · 35 citations

    2

    h-index

  5. PLoS Computational Biology

    2 publications · 308 citations

    2

    h-index

1–5