Cargando…
Condition-adaptive fused graphical lasso (CFGL): An adaptive procedure for inferring condition-specific gene co-expression network
Co-expression network analysis provides useful information for studying gene regulation in biological processes. Examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. One challenge in this type of analy...
Autores principales: | Lyu, Yafei, Xue, Lingzhou, Zhang, Feipeng, Koch, Hillary, Saba, Laura, Kechris, Katerina, Li, Qunhua |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173447/ https://www.ncbi.nlm.nih.gov/pubmed/30240439 http://dx.doi.org/10.1371/journal.pcbi.1006436 |
Ejemplares similares
-
RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks
por: Seal, Souvik, et al.
Publicado: (2023) -
Analysis of Twitter data with the Bayesian fused graphical lasso
por: Aflakparast, Mehran, et al.
Publicado: (2020) -
Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks
por: Wu, Nuosi, et al.
Publicado: (2019) -
An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning
por: Zhuang, Yonghua, et al.
Publicado: (2022) -
Inference of radio-responsive gene regulatory networks using the graphical lasso algorithm
por: Oh, Jung Hun, et al.
Publicado: (2014)