Search Engine Scoring Functions

Search Engine Scoring Functions is a computational methodology used in protein database search that quantifies the likelihood of a query sequence matching a database sequence by assigning a numerical score based on sequence alignment features, substitution matrices, gap penalties, and statistical models to distinguish biologically significant alignments from random matches.

5

Publications

393

Citations

22

Authors

9

Institutions

Publications per year

2017–2026

1

Authors

22

  1. EM
    Elizaveta M. Solovyeva

    Moscow Institute of Physics and Technology, Russia

    1 publications · 69 citations

    1

    h-index

  2. FB
    Florian Beck

    Max Planck Institute of Biochemistry, Germany

    1 publications · 49 citations

    1

    h-index

  3. MV
    Marc Vaudel

    University of Bergen, Norway

    1 publications · 49 citations

    1

    h-index

  4. ML
    M. L. Pridatchenko

    Institute of Energy Problems of Chemical Physics, Russia

    1 publications · 69 citations

    1

    h-index

  5. HD
    Huizhong Duan

    University of Illinois Urbana-Champaign, United States

    1 publications · 31 citations

    1

    h-index

1–5 of 22

Venues

  1. Journal of Proteome Research

    JPR · 2 publications · 95 citations

    2

    h-index

  2. Bioinformatics

    1 publications · 218 citations

    1

    h-index

  3. PROTEOMICS

    1 publications · 49 citations

    1

    h-index

1–3