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The term Big Data describes the approaches that are used for the manipulation of large amounts of information that are generated by different knowledge areas, such as Economics, Astronomy, Life Sciences, and Social Networks. Since the advent of Deep Sequencing technologies, which are characterized by large data production per run, Omics sciences require Big Data approaches. Thus, several fields of life science now rely highly on computational processing, large storage capacity, and new algorithms that perform traditional genomic, transcriptomic, and proteomic analyses with specific tools. The challenges that arise from large amounts of collected data (including processing, storage capacity, and sharing) will be overcome as new approaches and technological advances are developed. |
