Cluster-based Annotation

Cluster-Based Annotation is a metagenomic annotation method that assigns functional or taxonomic labels to sequencing reads or contigs by first grouping them into discrete sequence clusters based on similarity, then propagating annotations from representative or reference sequences within each cluster to all members.

25

Publications

3.8K

Citations

97

Authors

47

Institutions

Publications per year

2017–2026

7

Authors

97

  1. MB
    Mark Blaxter

    University of Edinburgh, United Kingdom

    2 publications · 211 citations

    2

    h-index

  2. DR
    Dominik R. Laetsch

    University of Edinburgh, United Kingdom

    1 publications · 113 citations

    1

    h-index

  3. FS
    Fabrizio Sebastiani

    Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo", Italy

    1 publications · 12 citations

    1

    h-index

  4. JP
    John Parkinson

    Hospital for Sick Children, Canada

    1 publications · 98 citations

    1

    h-index

  5. MF
    Michael F. Ochs

    Johns Hopkins University, United States

    1 publications · 28 citations

    1

    h-index

1–5 of 97

Venues

  1. Bioinformatics

    6 publications · 2.2K citations

    6

    h-index

  2. BMC Bioinformatics

    3 publications · 249 citations

    3

    h-index

  3. PubMed

    Repository · 2 publications · 71 citations

    2

    h-index

  4. Expert Systems with Applications

    1 publications · 23 citations

    1

    h-index

  5. Genes

    1 publications · 20 citations

    1

    h-index

1–5