Similarity Matrices

Similarity Matrices is a type of substitution matrix used in bioinformatics that quantifies the degree of evolutionary or functional resemblance between pairs of amino acids or nucleotides by assigning scores based on observed substitution frequencies and biochemical properties.

610

Publications

59.7K

Citations

1.7K

Authors

757

Institutions

Publications per year

2017–2026

155

Authors

1.7K

  1. RC
    Ramon Carbó‐Dorca

    Universitat de Girona, Spain

    10 publications · 363 citations

    10

    h-index

  2. CL
    Cheng Liang

    Shandong Normal University, China

    6 publications · 109 citations

    6

    h-index

  3. JL
    Jiawei Luo

    Hunan University, China

    5 publications · 92 citations

    5

    h-index

  4. FG
    Fei Guo

    Tianjin University, China

    4 publications · 177 citations

    4

    h-index

  5. RM
    Robert M. Guralnick

    University of Southern California, United States

    4 publications · 58 citations

    4

    h-index

1–5 of 1.7K

Venues

  1. Nucleic Acids Research

    13 publications · 3.4K citations

    12

    h-index

  2. Linear Algebra and its Applications

    18 publications · 368 citations

    12

    h-index

  3. Bioinformatics

    12 publications · 606 citations

    11

    h-index

  4. BMC Bioinformatics

    9 publications · 1.2K citations

    9

    h-index

  5. 8

    h-index

1–5