Biosequence Pattern Recognition

Biosequence Pattern Recognition is a computational methodology within sequence pattern recognition that specifically identifies biologically meaningful motifs, structures, or functional elements in nucleic acid, protein, or other molecular sequences through algorithmic analysis of their symbolic composition and context.

14

Publications

904

Citations

35

Authors

20

Institutions

Publications per year

2017–2026

2

Authors

35

  1. SL
    Stefano Lonardi

    University of California, Riverside, United States

    3 publications · 656 citations

    3

    h-index

  2. EK
    Eamonn Keogh

    University of California, Riverside, United States

    2 publications · 635 citations

    2

    h-index

  3. JV
    Jaak Vilo

    University of Tartu, Estonia

    2 publications · 59 citations

    2

    h-index

  4. BW
    B W Erickson

    Rockefeller University, United States

    1 publications · 32 citations

    1

    h-index

  5. AN
    Ajit Narayanan

    University of Exeter, United Kingdom

    1 publications · 16 citations

    1

    h-index

1–5 of 35

Venues

  1. 1

    h-index

  2. Information Sciences

    1 publications · 16 citations

    1

    h-index

  3. Purdue e-Pubs (Purdue University System)

    Repository · 1 publications · 21 citations

    1

    h-index

  4. Genetic Programming and Evolvable Machines

    1 publications · 18 citations

    1

    h-index

  5. Soft Computing

    1 publications · 14 citations

    1

    h-index

1–5