Data Scaling

Data Scaling is a data preprocessing technique in multi-omics analysis that standardizes the range of numerical features across different omics datasets to ensure uniformity and comparability by transforming variables to a common scale without distorting differences in the ranges of values.

85

Publications

5.7K

Citations

290

Authors

139

Institutions

Publications per year

2017–2026

25

Authors

290

  1. SN
    Shizuhiko Nishisato

    University of Toronto, Canada

    4 publications · 602 citations

    4

    h-index

  2. JM
    Jean–François Muzy

    Centre National de la Recherche Scientifique, France

    2 publications · 33 citations

    2

    h-index

  3. VÖ
    Viktor Öwall

    Lund University, Sweden

    2 publications · 86 citations

    2

    h-index

  4. SS
    Shmuel S. Oren

    University of California, Berkeley, United States

    2 publications · 343 citations

    2

    h-index

  5. NF
    Neal Fairley

    Teignmouth Community Hospital, United Kingdom

    2 publications · 36 citations

    2

    h-index

1–5 of 290

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 102 citations

    5

    h-index

  2. Surface and Interface Analysis

    SIA · 3 publications · 123 citations

    3

    h-index

  3. Psychometrika

    3 publications · 91 citations

    3

    h-index

  4. Management Science

    2 publications · 343 citations

    2

    h-index

  5. Pattern Recognition Letters

    2 publications · 286 citations

    2

    h-index

1–5