Partial Correlation Network Analysis

Partial Correlation Network Analysis is a statistical inference method that, within the context of gene co-expression analysis, identifies direct functional associations between pairs of genes by measuring the strength of their linear relationship after adjusting for the influence of all other genes in the network.

99

Publications

10K

Citations

462

Authors

263

Institutions

Publications per year

2017–2026

72

Authors

462

  1. EI
    Eiko I. Fried

    Leiden University, Netherlands

    7 publications · 3.3K citations

    7

    h-index

  2. DR
    Donald R. Williams

    University of California, Davis, United States

    6 publications · 487 citations

    6

    h-index

  3. SE
    Sacha Epskamp

    University of Amsterdam, Netherlands

    5 publications · 3.4K citations

    5

    h-index

  4. RJ
    Richard J. McNally

    Harvard University, United States

    5 publications · 874 citations

    5

    h-index

  5. PR
    Philippe Rast

    University of California, Davis, United States

    5 publications · 507 citations

    5

    h-index

1–5 of 462

Venues

  1. PLoS ONE

    5 publications · 213 citations

    5

    h-index

  2. Frontiers in Psychiatry

    4 publications · 163 citations

    4

    h-index

  3. International Journal of Eating Disorders

    3 publications · 186 citations

    3

    h-index

  4. Psychological Medicine

    3 publications · 474 citations

    3

    h-index

  5. Anxiety Stress & Coping

    2 publications · 200 citations

    2

    h-index

1–5