What time is it? Deep learning approaches for circadian rhythms.

ABSTRACT:

Motivation

Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken.

Results

We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic signals. We then use deep learning methods to develop and train BIO_CYCLE, a system to

SUBMITTER: Agostinelli F 

PROVIDER: S-EPMC4908327 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature