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Discovering differential genome sequence activity with interpretable and efficient deep learning
Discovering sequence features that differentially direct cells to alternate fates is key to understanding both cellular development and the consequences of disease related mutations. We introduce Expected Pattern Effect and Differential Expected Pattern Effect, two black-box methods that can interpr...
Autores principales: | Hammelman, Jennifer, Gifford, David K. |
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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/PMC8376110/ https://www.ncbi.nlm.nih.gov/pubmed/34370721 http://dx.doi.org/10.1371/journal.pcbi.1009282 |
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