Integration of genome-scale data identifies candidate sleep regulators.

Yin Yeng LeeMehari EndaleGang WuMarc D RubenLauren J FranceyAndrew R MorrisNatalie Y ChooRon C AnafiDavid F Smith Andrew C LiuJohn B Hogenesch

Published in: Sleep (2022)

Our study highlights the power of machine learning in integrating prior knowledge and genome-wide data to study genetic regulation of complex behaviors such as sleep.

Keyphrases

genome wide
machine learning
dna methylation
electronic health record
sleep quality
gene expression
artificial intelligence
copy number
depressive symptoms
deep learning