Loop Modeling Benchmarking

Loop Modeling Benchmarking is a formal evaluation framework that systematically assesses the accuracy, efficiency, and generalizability of computational methods for predicting protein loop conformations by comparing their performance against standardized datasets and established metrics.

10

Publications

690

Citations

34

Authors

11

Institutions

Publications per year

2017–2026

4

Authors

34

  1. YS
    Yi Shang

    University of Missouri, United States

    2 publications · 56 citations

    2

    h-index

  2. SP
    Son P. Nguyen

    University of Missouri, United States

    2 publications · 56 citations

    2

    h-index

  3. DX
    Dong Xu

    University of Missouri, United States

    2 publications · 56 citations

    2

    h-index

  4. JJ
    Jeffrey J. Gray

    Johns Hopkins University, United States

    2 publications · 156 citations

    2

    h-index

  5. BD
    Brian D. Weitzner

    Johns Hopkins University, United States

    2 publications · 156 citations

    2

    h-index

1–5 of 34

Venues

  1. PLoS ONE

    2 publications · 41 citations

    2

    h-index

  2. Journal of Computer-Aided Molecular Design

    1 publications · 25 citations

    1

    h-index

  3. Journal of Chemical Theory and Computation

    JCTC · 1 publications · 29 citations

    1

    h-index

  4. Proteins Structure Function and Bioinformatics

    1 publications · 104 citations

    1

    h-index

  5. The Journal of Immunology

    JI · 1 publications · 52 citations

    1

    h-index

1–5