Annotation Confidence Scoring

Annotation Confidence Scoring is a computational metric that quantifies the reliability of putative metabolite identifications by integrating evidence from spectral, chemical, and analytical data to distinguish high-confidence annotations from ambiguous or false assignments within metabolomics workflows.

21

Publications

2.5K

Citations

125

Authors

50

Institutions

Publications per year

2017–2026

12

Authors

125

  1. EC
    Emily C. Gentry

    University of California San Diego, United States

    2 publications · 360 citations

    2

    h-index

  2. MF
    Markus Fleischauer

    Friedrich Schiller University Jena, Germany

    2 publications · 360 citations

    2

    h-index

  3. ML
    Marcus Ludwig

    Friedrich Schiller University Jena, Germany

    2 publications · 360 citations

    2

    h-index

  4. SB
    Sebastian Böcker

    Friedrich Schiller University Jena, Germany

    2 publications · 360 citations

    2

    h-index

  5. MW
    Michael Witting

    Helmholtz Zentrum München, Germany

    2 publications · 360 citations

    2

    h-index

1–5 of 125

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 1 publications · 67 citations

    1

    h-index

  2. The ISME Journal

    1 publications · 94 citations

    1

    h-index

  3. Database

    1 publications · 1.4K citations

    1

    h-index

  4. Journal of Cheminformatics

    1 publications · 17 citations

    1

    h-index

  5. Talanta

    1 publications · 14 citations

    1

    h-index

1–5