Library Complexity Optimization

Library Complexity Optimization is a methodological framework in DNA shuffling that systematically enhances the diversity and quality of mutant libraries by balancing the representation of functional variants while minimizing redundancy and sequencing errors.

22

Publications

2.1K

Citations

154

Authors

73

Institutions

Publications per year

2017–2026

10

Authors

154

  1. AD
    Andrew D. Ellington

    The University of Texas at Austin, United States

    2 publications · 56 citations

    2

    h-index

  2. JD
    Jack D. Pollard

    The University of Texas at Austin, United States

    2 publications · 56 citations

    2

    h-index

  3. BC
    Brant C. Faircloth

    Louisiana State University, United States

    1 publications · 447 citations

    1

    h-index

  4. HS
    Hjalmar S. Kühl

    Max Planck Institute for Evolutionary Anthropology, Germany

    1 publications · 30 citations

    1

    h-index

  5. DA
    David A. Hughes

    University of Bristol, United Kingdom

    1 publications · 30 citations

    1

    h-index

1–5 of 154

Venues

  1. Current Protocols in Nucleic Acid Chemistry

    2 publications · 56 citations

    2

    h-index

  2. Molecular Ecology Resources

    2 publications · 75 citations

    2

    h-index

  3. BMC Genomics

    1 publications · 46 citations

    1

    h-index

  4. RNA

    1 publications · 26 citations

    1

    h-index

  5. Journal of Heredity

    1 publications · 209 citations

    1

    h-index

1–5