Proteomic Data Analysis

Proteomic Data Analysis is a computational and statistical methodology for interpreting complex protein expression, identification, and modification patterns derived from high-throughput proteomic experiments, distinguished by its focus on extracting biologically meaningful insights from mass spectrometry and associated omics data within clinical and translational research contexts.

11.5K

Publications

701.5K

Citations

61.7K

Authors

7.2K

Institutions

Publications per year

2017–2026

4.1K

Authors

61.7K

  1. RA
    Ruedi Aebersold

    ETH Zurich, Switzerland

    123 publications · 20.1K citations

    68

    h-index

  2. MM
    Matthias Mann

    Max Planck Institute of Biochemistry, Germany

    84 publications · 37.8K citations

    58

    h-index

  3. JR
    John R. Yates

    Scripps Research Institute, United States

    76 publications · 14K citations

    47

    h-index

  4. EW
    Eric W. Deutsch

    Institute for Systems Biology, United States

    65 publications · 9.9K citations

    43

    h-index

  5. RS
    Richard Smith

    Pacific Northwest National Laboratory, United States

    72 publications · 7.2K citations

    42

    h-index

1–5 of 61.7K

Venues

  1. Molecular & Cellular Proteomics

    MCP · 426 publications · 44.9K citations

    113

    h-index

  2. PROTEOMICS

    923 publications · 54.2K citations

    107

    h-index

  3. Journal of Proteome Research

    JPR · 910 publications · 51K citations

    100

    h-index

  4. Journal of Proteomics

    493 publications · 20.5K citations

    70

    h-index

  5. PLoS ONE

    394 publications · 16.7K citations

    66

    h-index

1–5