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Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks
Deep neural networks have demonstrated improved performance at predicting the sequence specificities of DNA- and RNA-binding proteins compared to previous methods that rely on k-mers and position weight matrices. To gain insights into why a DNN makes a given prediction, model interpretability method...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8118286/ https://www.ncbi.nlm.nih.gov/pubmed/33983921 http://dx.doi.org/10.1371/journal.pcbi.1008925 |