Common Feature Extraction

Common Feature Extraction is a computational methodology within consensus pharmacophore modeling that identifies invariant physicochemical and spatial characteristics shared across diverse ligands or receptor-bound conformations to define a unified pharmacophore hypothesis.

122

Publications

6.3K

Citations

491

Authors

207

Institutions

Publications per year

2017–2026

75

Authors

491

  1. KA
    Kiyoharu Aizawa

    The University of Tokyo, Japan

    2 publications · 130 citations

    2

    h-index

  2. YW
    Yunhong Wang

    Beihang University, China

    2 publications · 258 citations

    2

    h-index

  3. PV
    Prasad V. Bharatam

    National Institute of Pharmaceutical Education and Research, India

    2 publications · 24 citations

    2

    h-index

  4. SL
    Songtao Liu

    University of California, Santa Barbara, United States

    2 publications · 258 citations

    2

    h-index

  5. YZ
    Yu Zhang

    East China University of Science and Technology, China

    2 publications · 117 citations

    2

    h-index

1–5 of 491

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 116 citations

    5

    h-index

  2. IEEE Access

    4 publications · 303 citations

    4

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 403 citations

    2

    h-index

  4. IEEE Transactions on Robotics

    2 publications · 60 citations

    2

    h-index

  5. IEEE Transactions on Cybernetics

    2 publications · 139 citations

    2

    h-index

1–5