| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/bioinformatics/AgostinelliCSSB16 |
| P356 | DOI | 10.1093/BIOINFORMATICS/BTW243 |
| P932 | PMC publication ID | 4908327 |
| P698 | PubMed publication ID | 27307647 |
| P50 | author | Pierre Baldi | Q3383843 |
| Paolo Sassone-Corsi | Q3362664 | ||
| P2093 | author name string | Babak Shahbaba | |
| Nicholas Ceglia | |||
| Forest Agostinelli | |||
| P2860 | cites work | Analysis of gene regulatory networks in the mammalian circadian rhythm | Q21563498 |
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| CLOCK and BMAL1 regulate MyoD and are necessary for maintenance of skeletal muscle phenotype and function | Q33721678 | ||
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| Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules | Q34353087 | ||
| A circadian gene expression atlas in mammals: implications for biology and medicine | Q34445166 | ||
| High-fat diet disrupts behavioral and molecular circadian rhythms in mice | Q34710085 | ||
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| P275 | copyright license | Creative Commons Attribution-NonCommercial 4.0 International | Q34179348 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P433 | issue | 12 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | deep learning | Q197536 |
| circadian rhythm | Q208353 | ||
| P304 | page(s) | i8-i17 | |
| P577 | publication date | 2016-06-01 | |
| P1433 | published in | Bioinformatics | Q4914910 |
| P1476 | title | What time is it? Deep learning approaches for circadian rhythms | |
| P478 | volume | 32 |
| Q37556701 | CGDB: a database of circadian genes in eukaryotes |
| Q33719425 | CYCLOPS reveals human transcriptional rhythms in health and disease |
| Q55518663 | CircadiOmics: circadian omic web portal. |
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| Q36367440 | Compass in the data ocean: Toward chronotherapy |
| Q92442144 | Defining the Independence of the Liver Circadian Clock |
| Q98289863 | Genome-wide circadian regulation: A unique system for computational biology |
| Q42778393 | Guidelines for Genome-Scale Analysis of Biological Rhythms |
| Q33728740 | Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes. |
| Q62496193 | Learning in the Machine: Random Backpropagation and the Deep Learning Channel |
| Q55490211 | MICOP: Maximal information coefficient-based oscillation prediction to detect biological rhythms in proteomics data. |
| Q33602912 | The Synergistic Role of Light-Feeding Phase Relations on Entraining Robust Circadian Rhythms in the Periphery |
| Q57312120 | Universal method for robust detection of circadian state from gene expression |
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