Inferring Nonlinear Gene Regulatory Networks from Gene Expression Data Based on Distance Correlation

Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs). It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measure...

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Detalles Bibliográficos
Autores principales: Guo, Xiaobo, Zhang, Ye, Hu, Wenhao, Tan, Haizhu, Wang, Xueqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925093/
https://www.ncbi.nlm.nih.gov/pubmed/24551058
http://dx.doi.org/10.1371/journal.pone.0087446

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925093/
https://www.ncbi.nlm.nih.gov/pubmed/24551058
http://dx.doi.org/10.1371/journal.pone.0087446

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