Editing Efficiency Optimization

Editing Efficiency Optimization is a methodological framework within base editing research that systematically enhances the precision, specificity, and yield of targeted nucleotide modifications by refining experimental parameters, molecular components, and delivery strategies to maximize desired editing outcomes.

171

Publications

18.2K

Citations

1.3K

Authors

384

Institutions

Publications per year

2017–2026

156

Authors

1.3K

  1. DR
    David R. Liu

    Harvard University, United States

    12 publications · 4.7K citations

    12

    h-index

  2. XH
    Xingxu Huang

    ShanghaiTech University, China

    7 publications · 590 citations

    7

    h-index

  3. GA
    Gregory A. Newby

    Howard Hughes Medical Institute, United States

    7 publications · 3K citations

    7

    h-index

  4. CB
    Changhao Bi

    Tianjin Institute of Industrial Biotechnology, China

    6 publications · 200 citations

    6

    h-index

  5. JL
    Jordan L. Doman

    Broad Institute, United States

    6 publications · 2.3K citations

    6

    h-index

1–5 of 1.3K

Venues

  1. Nature Biotechnology

    19 publications · 7.8K citations

    19

    h-index

  2. Nature Communications

    19 publications · 1.3K citations

    19

    h-index

  3. Nucleic Acids Research

    11 publications · 571 citations

    11

    h-index

  4. Molecular Therapy — Nucleic Acids

    6 publications · 150 citations

    6

    h-index

  5. Nature Chemical Biology

    5 publications · 263 citations

    5

    h-index

1–5