Inferring Regulatory Networks From Mixed Observational Data Using Directed Acyclic Graphs

Construction of regulatory networks using cross-sectional expression profiling of genes is desired, but challenging. The Directed Acyclic Graph (DAG) provides a general framework to infer causal effects from observational data. However, most existing DAG methods assume that all nodes follow the same...

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Detalles Bibliográficos
Autores principales: Zhong, Wujuan, Dong, Li, Poston, Taylor B., Darville, Toni, Spracklen, Cassandra N., Wu, Di, Mohlke, Karen L., Li, Yun, Li, Quefeng, Zheng, Xiaojing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038820/
https://www.ncbi.nlm.nih.gov/pubmed/32127796
http://dx.doi.org/10.3389/fgene.2020.00008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038820/
https://www.ncbi.nlm.nih.gov/pubmed/32127796
http://dx.doi.org/10.3389/fgene.2020.00008

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