Structural Variant Detection

Structural Variant Detection is a computational method within genomic variant analysis that specifically identifies large-scale genomic alterations, such as deletions, duplications, inversions, and translocations, by distinguishing them from smaller variants through the analysis of sequencing data to infer structural differences in genome architecture.

226

Publications

47.6K

Citations

1.9K

Authors

601

Institutions

Publications per year

2017–2026

129

Authors

1.9K

  1. FJ
    Fritz J. Sedlazeck

    Baylor College of Medicine, United States

    15 publications · 3.4K citations

    15

    h-index

  2. EE
    Evan E. Eichler

    University of Washington, United States

    11 publications · 4.6K citations

    11

    h-index

  3. MC
    Michael C. Schatz

    Johns Hopkins University, United States

    8 publications · 2.5K citations

    8

    h-index

  4. YW
    Yadong Wang

    Harbin Institute of Technology, China

    6 publications · 741 citations

    8

    h-index

  5. FH
    Fereydoun Hormozdiari

    University of Washington, United States

    8 publications · 1.9K citations

    8

    h-index

1–5 of 1.9K

Venues

  1. Bioinformatics

    31 publications · 22.2K citations

    24

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 24 publications · 884 citations

    17

    h-index

  3. Genome biology

    16 publications · 4.9K citations

    17

    h-index

  4. PLoS ONE

    10 publications · 432 citations

    11

    h-index

  5. Nature Communications

    8 publications · 1.6K citations

    9

    h-index

1–5