Proteomic Data Normalization

Proteomic Data Normalization is a systematic computational procedure belonging to the class of data preprocessing techniques, specifically designed to minimize non-biological variability in proteomic datasets by adjusting for technical differences such as instrument bias, sample loading, and labeling efficiency while preserving true biological differences of interest.

106

Publications

14K

Citations

731

Authors

232

Institutions

Publications per year

2017–2026

35

Authors

731

  1. JR
    John R. Yates

    Scripps Research Institute, United States

    4 publications · 721 citations

    4

    h-index

  2. RS
    Richard Smith

    Pacific Northwest National Laboratory, United States

    4 publications · 1.4K citations

    4

    h-index

  3. JA
    Joshua Adkins

    Pacific Northwest National Laboratory, United States

    3 publications · 1.1K citations

    3

    h-index

  4. PC
    Paulo C. Carvalho

    Fundação Carlos Chagas, Brazil

    3 publications · 440 citations

    3

    h-index

  5. HH
    Henning Hermjakob

    European Bioinformatics Institute, United Kingdom

    3 publications · 69 citations

    3

    h-index

1–5 of 731

Venues

  1. Journal of Proteome Research

    JPR · 14 publications · 1.6K citations

    14

    h-index

  2. Molecular & Cellular Proteomics

    MCP · 10 publications · 5.9K citations

    10

    h-index

  3. PROTEOMICS

    8 publications · 544 citations

    8

    h-index

  4. Bioinformatics

    5 publications · 689 citations

    5

    h-index

  5. Methods in molecular biology

    Book series · 5 publications · 121 citations

    5

    h-index

1–5