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Predicting 3D genome folding from DNA sequence

By Geoffrey Fudenberg, David R. Kelley, Katherine S. Pollard

Posted 10 Oct 2019
bioRxiv DOI: 10.1101/800060

In interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Here we present a deep convolutional neural network, Akita, that accurately predicts genome folding from DNA sequence alone. Representations learned by Akita underscore the importance of CTCF and reveal a complex grammar underlying genome folding. Akita enables rapid in silico predictions for sequence mutagenesis, genome folding across species, and genetic variants.

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