Local Epigenomic Data are more Informative than Local Genome Sequence Data in Predicting Enhancer-Promoter Interactions Using Neural Networks

Enhancer-promoter interactions (EPIs) are crucial for transcriptional regulation. Mapping such interactions proves useful for understanding disease regulations and discovering risk genes in genome-wide association studies. Some previous studies showed that machine learning methods, as computational...

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Detalles Bibliográficos
Autores principales: Xiao, Mengli, Zhuang, Zhong, Pan, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016741/
https://www.ncbi.nlm.nih.gov/pubmed/31905774
http://dx.doi.org/10.3390/genes11010041

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7016741/
https://www.ncbi.nlm.nih.gov/pubmed/31905774
http://dx.doi.org/10.3390/genes11010041

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