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Big data in biology: The hope and present-day challenges in it

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GENE REPORTS
卷 21, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.genrep.2020.100869

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Big data; Cloud computing; Bioinformatics; High throughput data; MapReduce; Machine learning

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The wave of new technologies has opened up the opportunity for cost-effective generation of high-throughput profiles of biological systems. This is generating tons of biological data. It is thus leading us towards the big data era which is creating a pressing need to bridge the gap between high-throughput technological development and our ability for managing, analyzing, and integrating the biological big data. To harness the maximum out of it, sufficient expertise needs to be developed for big data management and analysis. In this review, we discuss the challenges related to storage, transfer, access and analysis of unstructured and structured biological big data. Subsequently, it provides a comprehensive summary regarding the important strategies adopted for biological big data management which includes a discussion on all the recently used tools or software built for high throughput processing and analysis of biological big data. Finally it discusses the future perspectives of big data bioinformatics.

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