Metabolite Data Processing

Metabolite Data Processing is a computational methodology that transforms raw analytical instrument outputs into biologically meaningful metabolite profiles through steps such as noise reduction, peak detection, alignment, normalization, and annotation within the workflow of metabolomics research.

534

Publications

86.8K

Citations

2.6K

Authors

927

Institutions

Publications per year

2017–2026

226

Authors

2.6K

  1. MR
    Mark R. Viant

    University of Birmingham, United Kingdom

    17 publications · 1.8K citations

    14

    h-index

  2. JX
    Jianguo Xia

    McGill University, Canada

    14 publications · 19.8K citations

    14

    h-index

  3. RM
    Reza M. Salek

    European Bioinformatics Institute, United Kingdom

    13 publications · 632 citations

    12

    h-index

  4. DS
    David S. Wishart

    University of Alberta, Canada

    11 publications · 19.7K citations

    11

    h-index

  5. GJ
    Gary J. Patti

    Washington University in St. Louis, United States

    11 publications · 2.8K citations

    11

    h-index

1–5 of 2.6K

Venues

  1. Analytical Chemistry

    72 publications · 16.5K citations

    45

    h-index

  2. Metabolomics

    51 publications · 4.8K citations

    36

    h-index

  3. Bioinformatics

    35 publications · 3.3K citations

    25

    h-index

  4. BMC Bioinformatics

    24 publications · 5.7K citations

    19

    h-index

  5. Metabolites

    20 publications · 1.5K citations

    18

    h-index

1–5