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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| 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 |