Gene Set Variation Analysis

Gene Set Variation Analysis is a computational method in pathway activity scoring that quantifies the enrichment of a gene set within a sample by analyzing the variation of gene expression rankings across predefined biological pathways, distinguishing it from other methods through its non-parametric, rank-based assessment of pathway activity without requiring a priori specification of class labels.

64

Publications

18.7K

Citations

483

Authors

198

Institutions

Publications per year

2017–2026

52

Variants

Gsva

Authors

483

  1. KF
    Kian Fan Chung

    Imperial College London, United Kingdom

    2 publications · 95 citations

    2

    h-index

  2. YC
    Yunxia Cui

    Shanghai Jiao Tong University, China

    2 publications · 45 citations

    2

    h-index

  3. AM
    Amin Moghaddas Gholami

    Technical University of Munich, Germany

    2 publications · 94 citations

    2

    h-index

  4. SW
    Siqiao Wang

    Tongji University, China

    2 publications · 24 citations

    2

    h-index

  5. ZH
    Zongqiang Huang

    First Affiliated Hospital of Zhengzhou University, China

    2 publications · 24 citations

    2

    h-index

1–5 of 483

Venues

  1. Frontiers in Immunology

    7 publications · 174 citations

    7

    h-index

  2. Frontiers in Genetics

    6 publications · 158 citations

    6

    h-index

  3. Aging

    4 publications · 82 citations

    3

    h-index

  4. Frontiers in Cell and Developmental Biology

    3 publications · 39 citations

    3

    h-index

  5. CNS Neuroscience & Therapeutics

    2 publications · 93 citations

    2

    h-index

1–5