Target Deconvolution Algorithms

Target Deconvolution Algorithms is a computational methodology that systematically infers the molecular targets of bioactive compounds by reversing phenotypic responses through algorithmic integration of omics data, chemical profiles, and interaction networks.

36

Publications

2.7K

Citations

257

Authors

116

Institutions

Publications per year

2017–2026

19

Authors

257

  1. RA
    Roman A. Zubarev

    Karolinska Institutet, Sweden

    4 publications · 225 citations

    4

    h-index

  2. RE
    Richard E. Higgs

    Eli Lilly (United States), United States

    3 publications · 69 citations

    3

    h-index

  3. BK
    Bernhard Küster

    Technical University of Munich, Germany

    3 publications · 1K citations

    3

    h-index

  4. GM
    Guillaume Médard

    Technical University of Munich, Germany

    3 publications · 1K citations

    3

    h-index

  5. JE
    John E. Hale

    Eli Lilly (United States), United States

    3 publications · 69 citations

    3

    h-index

1–5 of 257

Venues

  1. Journal of Chemical Information and Modeling

    JCIM · 3 publications · 393 citations

    3

    h-index

  2. Methods in molecular biology

    Book series · 3 publications · 83 citations

    3

    h-index

  3. Journal of Proteome Research

    JPR · 3 publications · 68 citations

    3

    h-index

  4. Nature Communications

    3 publications · 291 citations

    3

    h-index

  5. SLAS DISCOVERY

    2 publications · 65 citations

    2

    h-index

1–5