Partial Correlation Network Inference
Partial Correlation Network Inference is a statistical method for constructing regulatory networks by estimating pairwise conditional dependencies between variables, where the genus is network inference methods and the differentia is its use of partial correlation coefficients to identify direct interactions while controlling for the influence of other variables.
37
Publications
2.8K
Citations
144
Authors
98
Institutions
Publications per year
2017–2026
16
37
Eiko I. Fried, Marloes B. Eidhof, Sabina Palić et al. · Clinical Psychological Science · 2018 · 481 citations · Full text
Medicine, Psychiatry, Psychology +13
Biotic interactions hold the key to understanding metacommunity organisation
Jorge García‐Girón, Jani Heino, Francisco García‐Criado et al. · Ecography · 2020 · 128 citations · Full text
Life Sciences, Biology, Ecology +17
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98

SIB Swiss Institute of Bioinformatics
Lausanne, Switzerland
2 h-index
4 publications
564 citations
NHS Lothian
Edinburgh, United Kingdom
2 h-index
2 publications
137 citations

University of Amsterdam
Amsterdam, The Netherlands
2 h-index
3 publications
613 citations
University of Vienna
Vienna, Austria
2 h-index
4 publications
274 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
12 publications
429 citations
ETH Zurich
Zurich, Switzerland
2 h-index
4 publications
564 citations
Virginia Tech
Blacksburg, United States
2 h-index
6 publications
2.3K citations
Inserm
Paris, France
2 h-index
5 publications
481 citations
1–8 of 98
3 publications · 157 citations
3
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Repository · 2 publications · 35 citations
2
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2 publications · 815 citations
2
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1 publications · 38 citations
1
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1 publications · 22 citations
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