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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.<\/jats:p><jats:p>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 robustly estimate which signals are periodic in high-throughput circadian experiments, producing estimates of amplitudes, periods, phases, as well as several statistical significance measures. Using the curated data, BIO_CYCLE is compared to other approaches and shown to achieve state-of-the-art performance across multiple metrics. We then use deep learning methods to develop and train BIO_CLOCK to robustly estimate 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\u2009h, using the expression levels of only a small number of core clock genes. BIO_CLOCK is shown to work reasonably well across tissue types, and often with only small degradation across conditions. BIO_CLOCK is used to annotate most mouse experiments found in the GEO database with an inferred time stamp.<\/jats:p><jats:p>Availability and Implementation: All data and software are publicly available on the CircadiOmics web portal: circadiomics.igb.uci.edu\/.<\/jats:p><jats:p>Contacts: \u00a0fagostin@uci.edu or pfbaldi@uci.edu<\/jats:p><jats:p>Supplementary information \u00a0: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw243","type":"journal-article","created":{"date-parts":[[2016,6,15]],"date-time":"2016-06-15T15:43:52Z","timestamp":1466005432000},"page":"i8-i17","source":"Crossref","is-referenced-by-count":90,"title":["What time is it? 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