NCNet: Deep Learning Network Models for Predicting Function of Non-coding DNA

The human genome consists of 98.5% non-coding DNA sequences, and most of them have no known function. However, a majority of disease-associated variants lie in these regions. Therefore, it is critical to predict the function of non-coding DNA. Hence, we propose the NCNet, which integrates deep resid...

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Detalles Bibliográficos
Autores principales: Zhang, Hanyu, Hung, Che-Lun, Liu, Meiyuan, Hu, Xiaoye, Lin, Yi-Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6549219/
https://www.ncbi.nlm.nih.gov/pubmed/31191597
http://dx.doi.org/10.3389/fgene.2019.00432

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6549219/
https://www.ncbi.nlm.nih.gov/pubmed/31191597
http://dx.doi.org/10.3389/fgene.2019.00432

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