Computational Specificity Models

Computational Specificity Models is a systematic framework that integrates predictive algorithms and bioinformatics analyses to quantify and minimize off-target effects in genome editing by modeling the binding affinity and cleavage activity of nucleases across non-target genomic sites.

37

Publications

2.4K

Citations

183

Authors

82

Institutions

Publications per year

2017–2026

21

Authors

183

  1. RG
    Raluca Gordân

    Duke University, United States

    3 publications · 92 citations

    3

    h-index

  2. DV
    Dionne Vafeados

    University of Washington, United States

    2 publications · 50 citations

    2

    h-index

  3. IG
    Inna Goreshnik

    University of Washington, United States

    2 publications · 50 citations

    2

    h-index

  4. HK
    Hugh K. Haddox

    University of Washington, United States

    2 publications · 50 citations

    2

    h-index

  5. JC
    James C. Whisstock

    Monash University, Australia

    2 publications · 130 citations

    2

    h-index

1–5 of 183

Venues

  1. Nucleic Acids Research

    5 publications · 450 citations

    5

    h-index

  2. Nature Communications

    5 publications · 640 citations

    4

    h-index

  3. Bioinformatics

    2 publications · 55 citations

    2

    h-index

  4. Current Topics in Medicinal Chemistry

    2 publications · 50 citations

    2

    h-index

  5. PLoS Biology

    2 publications · 96 citations

    2

    h-index

1–5