High-throughput Sequence Visualization

High-Throughput Sequence Visualization is a computational visualization approach that enables the efficient representation and analysis of large-scale biological sequence data generated by high-throughput sequencing technologies, distinguished by its capacity to handle massive volumes of sequence reads with scalability, speed, and information retention.

105

Publications

41.8K

Citations

489

Authors

210

Institutions

Publications per year

2017–2026

42

Authors

489

  1. WD
    Wouter De Coster

    VIB-UAntwerp Center for Molecular Neurology, Belgium

    3 publications · 4.2K citations

    3

    h-index

  2. CV
    Christine Van Broeckhoven

    University of Antwerp, Belgium

    3 publications · 3.4K citations

    3

    h-index

  3. NH
    Nadine Holmes

    University of Nottingham, United Kingdom

    2 publications · 394 citations

    2

    h-index

  4. VK
    Vardhman K. Rakyan

    Queen Mary University of London, United Kingdom

    2 publications · 394 citations

    2

    h-index

  5. SK
    Surendra Kumar

    Memorial University of Newfoundland, Canada

    2 publications · 48 citations

    2

    h-index

1–5 of 489

Venues

  1. Bioinformatics

    35 publications · 14.4K citations

    27

    h-index

  2. Nucleic Acids Research

    13 publications · 17.4K citations

    12

    h-index

  3. BMC Bioinformatics

    10 publications · 347 citations

    10

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 7 publications · 265 citations

    7

    h-index

  5. Briefings in Bioinformatics

    6 publications · 1.3K citations

    6

    h-index

1–5