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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...

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Detalles Bibliográficos
Autores principales: Hammelman, Jennifer, Gifford, David K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
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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