Template-free Modeling

Template-Free Modeling is a structure prediction approach that generates three-dimensional molecular or protein conformations without relying on known experimental structures as templates, distinguishing it from template-based methods by employing de novo sampling and energy minimization techniques to predict native folds from sequence or composition alone.

95

Publications

8.1K

Citations

344

Authors

141

Institutions

Publications per year

2017–2026

49

Variants

Ab Initio ModelingDe Novo Modeling

Authors

344

  1. YZ
    Yang Zhang

    University of Michigan, United States

    8 publications · 2.2K citations

    8

    h-index

  2. AK
    Andriy Kryshtafovych

    University of California, Davis, United States

    6 publications · 589 citations

    7

    h-index

  3. JC
    Jianlin Cheng

    University of Missouri, United States

    5 publications · 185 citations

    5

    h-index

  4. JX
    Jinbo Xu

    Toyota Technological Institute at Chicago, United States

    5 publications · 369 citations

    5

    h-index

  5. CY
    Chaochao Yan

    Northwest University, China

    4 publications · 119 citations

    4

    h-index

1–5 of 344

Venues

  1. Proteins Structure Function and Bioinformatics

    30 publications · 4.1K citations

    24

    h-index

  2. ChemRxiv

    Repository · 5 publications · 145 citations

    5

    h-index

  3. Bioinformatics

    4 publications · 196 citations

    4

    h-index

  4. BMC Bioinformatics

    2 publications · 49 citations

    2

    h-index

  5. Chemical Science

    2 publications · 277 citations

    2

    h-index

1–5