Sequence-based Function Prediction

Sequence-Based Function Prediction is a computational approach within protein function annotation that infers the biological function of a protein solely from its amino acid sequence by identifying evolutionary, structural, or physicochemical patterns conserved among functionally characterized homologs.

385

Publications

55.7K

Citations

1.3K

Authors

520

Institutions

Publications per year

2017–2026

121

Variants

Sequence-based Protein Function Prediction

Authors

1.3K

  1. DK
    Daisuke Kihara

    Purdue University West Lafayette, United States

    8 publications · 519 citations

    8

    h-index

  2. RD
    Ross D. King

    Aberystwyth University, United Kingdom

    8 publications · 447 citations

    8

    h-index

  3. YC
    Yu‐Dong Cai

    Shanghai University, China

    7 publications · 649 citations

    7

    h-index

  4. AC
    Amanda Clare

    Aberystwyth University, United Kingdom

    7 publications · 433 citations

    7

    h-index

  5. CO
    Christine Orengo

    University College London, United Kingdom

    7 publications · 347 citations

    7

    h-index

1–5 of 1.3K

Venues

  1. Bioinformatics

    42 publications · 16.2K citations

    30

    h-index

  2. Nucleic Acids Research

    31 publications · 7.6K citations

    30

    h-index

  3. BMC Bioinformatics

    29 publications · 2.1K citations

    22

    h-index

  4. PLoS ONE

    17 publications · 985 citations

    14

    h-index

  5. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 19 publications · 1.2K citations

    14

    h-index

1–5