The ‘un-shrunk’ partial correlation in Gaussian graphical models

The ‘un-shrunk’ partial correlation in Gaussian graphical models

Background: In systems biology, it is important to reconstruct regulatory networks from quantitative molecular profiles. Gaussian graphical models (GGMs) are one of the most popular methods to this end. A GGM consists of nodes (representing the transcripts, metabolites or proteins) inter-connected b...

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Bibliographic Details
Main Authors: Bernal, V. (Author), Bischoff, R. (Author), Grzegorczyk, M. (Author), Guryev, V. (Author), Horvatovich, P. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
animal
animal experiment
Animals
article
Biological interpretation
Correlation methods
Elastic moduli
Escherichia coli
Gaussian graphical models
Gene expression
Gene expression datasets
gene regulatory network
Gene regulatory networks
Graphic methods
High-dimensional problems
learning
male
Metabolites
Mice
mouse
Mus musculus
nonhuman
normal distribution
Normal Distribution
Partial correlation
Partial correlations
Regulatory network
Shrinkage
Shrinkage methods
Shrinkage value
systems biology
Systems Biology
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