Cloud Computing Enabled Big Multi-Omics Data Analytics

High-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.

Automated summary

High-throughput experiments allow researchers to explore complex multifactorial diseases through large-scale analysis of omics data. Cloud computing is proving increasingly useful in molecular modeling, omics data analytics, and the integration, analysis, and interpretation of phenotypic data. Recent innovations in computational technologies, especially in cloud computing, offer a promising, low-cost, and highly flexible solution for processing and analyzing omics data.