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PEDLA: predicting enhancers with a deep learning-based algorithmic framework
Transcriptional enhancers are non-coding segments of DNA that play a central role in the spatiotemporal regulation of gene expression programs. However, systematically and precisely predicting enhancers remain a major challenge. Although existing methods have achieved some success in enhancer predic...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4916453/ https://www.ncbi.nlm.nih.gov/pubmed/27329130 http://dx.doi.org/10.1038/srep28517 |