A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation.

Cell64.50
Volume: 178, Issue: 1, Pages: 91
Published: Jun 27, 2019
Abstract
Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequence alone. We trained our model (APARENT, APA REgression NeT) on isoform expression data from over 3 million APA reporters. APARENT's predictions are highly accurate when tasked with inferring APA in synthetic and human 3'UTRs. Visualizing features learned across all network layers reveals that...
Paper Details
Title
A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation.
Published Date
Jun 27, 2019
Journal
Volume
178
Issue
1
Pages
91
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