Distance Constraint Averaging

Distance Constraint Averaging is a computational method in consensus pharmacophore modeling that integrates spatial constraints from multiple pharmacophore models by calculating the mean inter-feature distances to derive a refined, representative pharmacophore hypothesis.

5

Publications

174

Citations

14

Authors

9

Institutions

Publications per year

2017–2026

1

Authors

14

  1. HA
    Harold A. Scheraga

    Cornell University, United States

    2 publications · 70 citations

    2

    h-index

  2. HW
    Hiroshi Wako

    Waseda University, Japan

    2 publications · 70 citations

    2

    h-index

  3. ML
    María Luisa Tasayco

    City College of New York, United States

    1 publications · 33 citations

    1

    h-index

  4. TF
    Thomas F. Jenny

    ETH Zurich, Switzerland

    1 publications · 16 citations

    1

    h-index

  5. DR
    Dennis R. Livesay

    University of North Carolina at Charlotte, United States

    1 publications · 33 citations

    1

    h-index

1–5 of 14

Venues

  1. Journal of Protein Chemistry

    2 publications · 70 citations

    2

    h-index

  2. Journal of Molecular Biology

    JMB · 1 publications · 33 citations

    1

    h-index

  3. The Journal of Chemical Physics

    1 publications · 55 citations

    1

    h-index

  4. Folding and Design

    1 publications · 16 citations

    1

    h-index

  5. Expert Systems with Applications

    1 publications · 11 citations

1–5