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In the past decade, the volume of "omics" data generated by the different high-throughput technologies has expanded exponentially. The managing, storing, and analyzing of this big data have been a great challenge for the researchers, especially when moving towards the goal of generating testable data-driven hypotheses, which has been the promise of the high-throughput experimental techniques. Different bioinformatics approaches have been developed to streamline the downstream analyzes bydoi:10.1155/2017/6213474 pmid:28331849 pmcid:PMC5346376 fatcat:7yhwtsgyqndabcrhpx7uxsx7da