Cloud computing enabled big multi-omics data analytics

Saraswati Koppad; Annappa B; Georgios V Gkoutos; Animesh Acharjee

doi:10.1177/11779322211035921

Cloud computing enabled big multi-omics data analytics

Saraswati Koppad, Annappa B, Georgios V Gkoutos, Animesh Acharjee

Cancer and Genomic Sciences

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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.

Original language	English
Pages (from-to)	1-16
Number of pages	16
Journal	Bioinformatics and Biology Insights
Volume	15
Early online date	28 Jul 2021
DOIs	https://doi.org/10.1177/11779322211035921
Publication status	Published - Dec 2021

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Ministry of Electronics and Information Technology (MeitY), Government of India. AA and GVG acknowledge support from the National Institute for Health Research (NIHR) Birmingham Experimental Cancer Medicine Centre (ECMC), NIHR Birmingham Surgical Reconstruction and Microbiology Research Centre (SRMRC), Nanocommons H2020-EU (731032) and the NIHR Birmingham Biomedical Research Centre, and the MRC (Medical Research Council) Health Data Research UK (HDRUK/CFC/01), an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities. The views expressed in this publication are those of the authors and do not necessarily represent those of the National Health Service (NHS), the NIHR, the MRC, or the Department of Health.

Publisher Copyright:
© The Author(s) 2021.

Keywords

Big data
cloud computing
multi-omics data
data analytics
data integration

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Cite this

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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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note = "Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Ministry of Electronics and Information Technology (MeitY), Government of India. AA and GVG acknowledge support from the National Institute for Health Research (NIHR) Birmingham Experimental Cancer Medicine Centre (ECMC), NIHR Birmingham Surgical Reconstruction and Microbiology Research Centre (SRMRC), Nanocommons H2020-EU (731032) and the NIHR Birmingham Biomedical Research Centre, and the MRC (Medical Research Council) Health Data Research UK (HDRUK/CFC/01), an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities. The views expressed in this publication are those of the authors and do not necessarily represent those of the National Health Service (NHS), the NIHR, the MRC, or the Department of Health. Publisher Copyright: {\textcopyright} The Author(s) 2021.",

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Cloud computing enabled big multi-omics data analytics

Abstract

Bibliographical note

Keywords

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