Imputing missing RNA-sequencing data from DNA methylation by using a transfer learning–based neural network

BACKGROUND: Gene expression plays a key intermediate role in linking molecular features at the DNA level and phenotype. However, owing to various limitations in experiments, the RNA-seq data are missing in many samples while there exist high-quality of DNA methylation data. Because DNA methylation i...

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Detalles Bibliográficos
Autores principales: Zhou, Xiang, Chai, Hua, Zhao, Huiying, Luo, Ching-Hsing, Yang, Yuedong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350980/
https://www.ncbi.nlm.nih.gov/pubmed/32649756
http://dx.doi.org/10.1093/gigascience/giaa076

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350980/
https://www.ncbi.nlm.nih.gov/pubmed/32649756
http://dx.doi.org/10.1093/gigascience/giaa076

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