RT Journal Article
SR Electronic
T1 Predicting 3D genome folding from DNA sequence
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 800060
DO 10.1101/800060
A1 Fudenberg, Geoff
A1 Kelley, David R.
A1 Pollard, Katherine S.
YR 2019
UL http://biorxiv.org/content/early/2019/10/10/800060.abstract
AB 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.