A machine learning method to detect molecular species that oscillate in high-throughput circadian experiments. BIO_CLOCK estimates the time at which a particular single-time-point transcriptomic experiment was carried. In most cases, BIO_CLOCK can reliably predict time, within approximately 1 h, using the expression levels of only a small number of core clock genes. BIO_CLOCK is used to annotate most mouse experiments found in the Gene Expression Omnibus database with an inferred time stamp.
Department of Computer Science, University of California-Irvine, Irvine, CA, USA; Department of Statistics, University of California-Irvine, Irvine, CA, USA; Department of Biological Chemistry, University of California-Irvine, Irvine, CA, USA
BIO_CLOCK funding source(s)
This work was supported by grants from the National Science Foundation (NSF IIS-1550705) and the National Institutes of Health (NIH DA 036984).