Sequence Motif Discovery

Sequence Motif Discovery is a computational method in bioinformatics that identifies statistically significant, recurring patterns in biological sequences by distinguishing them from background variation through specialized algorithms and probabilistic models.

1.3K

Publications

134.6K

Citations

4.5K

Authors

1.2K

Institutions

Publications per year

2017–2026

163

Authors

4.5K

  1. TL
    Timothy L. Bailey

    The University of Queensland, Australia

    29 publications · 27.3K citations

    24

    h-index

  2. EK
    Eamonn Keogh

    University of California, Riverside, United States

    16 publications · 2.9K citations

    15

    h-index

  3. MT
    Martin Tompa

    University of Washington, United States

    10 publications · 1.5K citations

    10

    h-index

  4. SR
    Sanguthevar Rajasekaran

    University of Connecticut, United States

    10 publications · 392 citations

    10

    h-index

  5. WS
    William Stafford Noble

    University of Washington, United States

    10 publications · 19.3K citations

    10

    h-index

1–5 of 4.5K

Venues

  1. Nucleic Acids Research

    127 publications · 31.7K citations

    57

    h-index

  2. Bioinformatics

    133 publications · 16.5K citations

    48

    h-index

  3. BMC Bioinformatics

    72 publications · 4.7K citations

    31

    h-index

  4. Proceedings of the National Academy of Sciences

    PNAS · 33 publications · 6.3K citations

    30

    h-index

  5. Journal of Biological Chemistry

    JBC · 36 publications · 2.3K citations

    29

    h-index

1–5