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Learning and interpreting the gene regulatory grammar in a deep learning framework
Deep neural networks (DNNs) have achieved state-of-the-art performance in identifying gene regulatory sequences, but they have provided limited insight into the biology of regulatory elements due to the difficulty of interpreting the complex features they learn. Several models of how combinatorial b...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660921/ https://www.ncbi.nlm.nih.gov/pubmed/33137083 http://dx.doi.org/10.1371/journal.pcbi.1008334 |