Integrating Expression Data-Based Deep Neural Network Models with Biological Networks to Identify Regulatory Modules for Lung Adenocarcinoma

SIMPLE SUMMARY: The growing evidence suggested that competing endogenous RNAs (ceRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of them in lung adenocarcinoma remains unclear. Identification of the regulatory modules for lung adenocarcinoma is...

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Detalles Bibliográficos
Autores principales: Fu, Lei, Luo, Kai, Lv, Junjie, Wang, Xinyan, Qin, Shimei, Zhang, Zihan, Sun, Shibin, Wang, Xu, Yun, Bei, He, Yuehan, He, Weiming, Li, Wan, Chen, Lina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9495551/
https://www.ncbi.nlm.nih.gov/pubmed/36138770
http://dx.doi.org/10.3390/biology11091291

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9495551/
https://www.ncbi.nlm.nih.gov/pubmed/36138770
http://dx.doi.org/10.3390/biology11091291

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