Cloud computing enabled big multi-omics data analytics.
Koppad, Saraswati B, Annappa Gkoutos, Georgios V Acharjee, Animesh
Koppad, Saraswati
B, Annappa
Gkoutos, Georgios V
Acharjee, Animesh
Abstract
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.
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Date
2021-07-28
Type
Article
Subject
Oncology. Pathology., Genetics, Surgery, Microbiology. Immunology
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Citation
Koppad S, B A, Gkoutos GV, Acharjee A. Cloud Computing Enabled Big Multi-Omics Data Analytics. Bioinform Biol Insights. 2021 Jul 28;15:11779322211035921. doi: 10.1177/11779322211035921
Journal / Source Title
Bioinformatics and Biology Insights
DOI
10.1177/11779322211035921
PMID
34376975
Publisher
SAGE Publications
Publisher’s URL
https://journals.sagepub.com/home/bbi