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An intrinsically interpretable neural network architecture for sequence to function learning
MOTIVATION: Sequence-based deep learning approaches have been shown to predict a multitude of functional genomic readouts, including regions of open chromatin and RNA expression of genes. However, a major limitation of current methods is that model interpretation relies on computationally demanding...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Cold Spring Harbor Laboratory
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900791/ https://www.ncbi.nlm.nih.gov/pubmed/36747873 http://dx.doi.org/10.1101/2023.01.25.525572 |