Structural Variant Visualization

Structural Variant Visualization is a genomic data visualization method that specifically represents large-scale DNA alterations, such as deletions, duplications, inversions, and translocations, by encoding their type, genomic location, and structural relationship to reference sequences and other genomic features.

23

Publications

1.1K

Citations

164

Authors

70

Institutions

Publications per year

2017–2026

14

Authors

164

  1. MS
    Marc Salit

    National Institute of Standards and Technology, United States

    2 publications · 74 citations

    2

    h-index

  2. WT
    William T. Harvey

    University of Washington, United States

    2 publications · 51 citations

    2

    h-index

  3. MC
    Michael C. Schatz

    Johns Hopkins University, United States

    2 publications · 155 citations

    2

    h-index

  4. JM
    Justin M. Zook

    National Institute of Standards and Technology, United States

    2 publications · 74 citations

    2

    h-index

  5. NS
    Noah Spies

    Stanford University, United States

    2 publications · 74 citations

    2

    h-index

1–5 of 164

Venues

  1. Bioinformatics

    6 publications · 278 citations

    6

    h-index

  2. BMC Bioinformatics

    3 publications · 108 citations

    3

    h-index

  3. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 3 publications · 91 citations

    3

    h-index

  4. Nucleic Acids Research

    2 publications · 98 citations

    2

    h-index

  5. PeerJ

    2 publications · 32 citations

    2

    h-index

1–5