Learning Gaussian graphical models from correlated data

Gaussian Graphical Models (GGMs) are a type of network modeling that uses partial correlation rather than correlation for representing complex relationships among multiple variables. The advantage of using partial correlation is to show the relation between two variables after “adjusting” for the ef...

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Bibliographic Details
Published in:Frontiers in Systems Biology
Main Authors: Zeyuan Song, Sophia Gunn, Stefano Monti, Gina M. Peloso, Ching-Ti Liu, Kathryn Lunetta, Paola Sebastiani
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Subjects:
Gaussian graphical models
corelated data
bootstrap
polygenic risk score
partial correlation
Online Access:https://www.frontiersin.org/articles/10.3389/fsysb.2025.1589079/full

Internet

https://www.frontiersin.org/articles/10.3389/fsysb.2025.1589079/full

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