Cloud Computing Enabled Big Multi-Omics Data Analytics

dc.contributor.authorKoppad, S.
dc.contributor.authorB, A.
dc.contributor.authorGkoutos, G.V.
dc.contributor.authorAcharjee, A.
dc.date.accessioned2026-02-08T18:38:54Z
dc.date.issued2021
dc.description.abstractHigh-throughput experiments enable researchers to explore complex multifactorial diseases through large-scale analysis of omics data. Challenges for such high-dimensional data sets include storage, analyses, and sharing. Recent innovations in computational technologies and approaches, especially in cloud computing, offer a promising, low-cost, and highly flexible solution in the bioinformatics domain. Cloud computing is rapidly proving increasingly useful in molecular modeling, omics data analytics (eg, RNA sequencing, metabolomics, or proteomics data sets), and for the integration, analysis, and interpretation of phenotypic data. We review the adoption of advanced cloud-based and big data technologies for processing and analyzing omics data and provide insights into state-of-the-art cloud bioinformatics applications. © The Author(s) 2021.
dc.identifier.citationBioinformatics and Biology Insights, 2021, Vol.15, , p. -
dc.identifier.issn11779322
dc.identifier.urihttps://doi.org/10.1177/11779322211035921
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/34415
dc.publisherSAGE Publications Inc.
dc.subjectBig data
dc.subjectcloud computing
dc.subjectdata analytics
dc.subjectdata integration
dc.subjectmulti-omics data
dc.titleCloud Computing Enabled Big Multi-Omics Data Analytics

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