Long-read Variant Detection

Long-Read Variant Detection is a computational method in genomic analysis that identifies genetic variants from long-read sequencing data, distinguished by its ability to resolve complex and structural variations through the analysis of continuous, high-molecular-weight DNA sequences.

96

Publications

8.8K

Citations

843

Authors

326

Institutions

Publications per year

2017–2026

90

Authors

843

  1. FJ
    Fritz J. Sedlazeck

    Baylor College of Medicine, United States

    15 publications · 2.9K citations

    15

    h-index

  2. MM
    Medhat Mahmoud

    Baylor College of Medicine, United States

    8 publications · 2.3K citations

    8

    h-index

  3. MC
    Michael C. Schatz

    Johns Hopkins University, United States

    8 publications · 2.5K citations

    8

    h-index

  4. JM
    Justin M. Zook

    National Institute of Standards and Technology, United States

    6 publications · 2.2K citations

    6

    h-index

  5. EE
    Evan E. Eichler

    University of Washington, United States

    6 publications · 617 citations

    6

    h-index

1–5 of 843

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 16 publications · 727 citations

    15

    h-index

  2. Bioinformatics

    6 publications · 507 citations

    6

    h-index

  3. Nature Communications

    6 publications · 367 citations

    6

    h-index

  4. Genome biology

    6 publications · 836 citations

    6

    h-index

  5. Frontiers in Genetics

    4 publications · 99 citations

    4

    h-index

1–5