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RhythmicDB: A Database of Predicted Multi-Frequency Rhythmic Transcripts
Stefano Castellana1, Tommaso Biagini1, Francesco Petrizzelli1
1Bioinformatics Unit, Fondazione IRCCS Casa Sollievo Della Sofferenza, San Giovanni Rotondo, Italy.
Abstract:
The physiology and behavior of living organisms are featured by time-related variations driven by molecular clockworks that arose during evolution stochastically and heterogeneously. Over the years, several high-throughput experiments were performed to evaluate time-dependent gene expression in different cell types across several species and experimental conditions. Here, these were retrieved, manually curated, and analyzed by two software packages, BioCycle and MetaCycle, to infer circadian or ultradian transcripts across different species. These transcripts were stored in RhythmicDB and made publically available.
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