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Testing Differential Gene Networks under Nonparanormal Graphical Models with False Discovery Rate Control

The nonparanormal graphical model has emerged as an important tool for modeling dependency structure between variables because it is flexible to non-Gaussian data while maintaining the good interpretability and computational convenience of Gaussian graphical models. In this paper, we consider the pr...

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Detalles Bibliográficos
Autor principal: Zhang, Qingyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073847/
https://www.ncbi.nlm.nih.gov/pubmed/32033447
http://dx.doi.org/10.3390/genes11020167