Cloud Computing Enabled Big Multi-Omics Data Analytics

被引:20
|
作者
Koppad, Saraswati [1 ]
Annappa, B. [1 ]
Gkoutos, Georgios, V [2 ,3 ,4 ,5 ,6 ,7 ,8 ]
Acharjee, Animesh [2 ,3 ,4 ,5 ]
机构
[1] Natl Inst Technol Karnataka, Dept Comp Sci & Engn, Surathkal, India
[2] Univ Birmingham, Coll Med & Dent Sci, Inst Canc & Genom Sci, Birmingham B15 2TT, W Midlands, England
[3] Univ Birmingham, Coll Med & Dent Sci, Ctr Computat Biol, Birmingham B15 2TT, W Midlands, England
[4] Univ Hosp Birmingham NHS Fdn Trust, Inst Translat Med, Birmingham, W Midlands, England
[5] Univ Hosp Birmingham, NIHR Surg Reconstruct & Microbiol Res Ctr, Birmingham, W Midlands, England
[6] MRC Hlth Data Res UK HDR UK, London, England
[7] NIHR Expt Canc Med Ctr, Birmingham, W Midlands, England
[8] Univ Hosp Birmingham, NIHR Biomed Res Ctr, Birmingham, W Midlands, England
来源
基金
欧盟地平线“2020”; 英国医学研究理事会; 英国科研创新办公室;
关键词
Big data; cloud computing; multi-omics data; data analytics; data integration; CANCER GENOMICS CLOUD; SEQUENCING DATA; FRAMEWORK; TOOLKIT; COST;
D O I
10.1177/11779322211035921
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Multi-omics Multi-scale Big Data Analytics for Cancer Genomics
    Agarwal, Mahima
    Adhil, Mohamood
    Talukder, Asoke K.
    [J]. BIG DATA ANALYTICS, BDA 2015, 2015, 9498 : 228 - 243
  • [2] Perspectives of using Cloud computing in integrative analysis of multi-omics data
    Augustyn, Dariusz R.
    Wycislik, Lukasz
    Mrozek, Dariusz
    [J]. BRIEFINGS IN FUNCTIONAL GENOMICS, 2021, 20 (04) : 198 - 206
  • [3] Advances in cloud computing and big data analytics
    Dong, Fang
    Shen, Jun
    He, Qiang
    [J]. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2018, 30 (20):
  • [4] Big data analytics in Cloud computing: an overview
    Berisha, Blend
    Meziu, Endrit
    Shabani, Isak
    [J]. JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 2022, 11 (01):
  • [5] Big data analytics in Cloud computing: an overview
    Blend Berisha
    Endrit Mëziu
    Isak Shabani
    [J]. Journal of Cloud Computing, 11
  • [6] Big data analytics in Cloud computing: an overview
    Berisha, Blend
    Mëziu, Endrit
    Shabani, Isak
    [J]. Journal of Cloud Computing, 2022, 11 (01)
  • [7] Challenges of Cloud Computing & Big Data Analytics
    Gupta, Anita
    Mehrotra, Abhay
    Khan, P. M.
    [J]. 2015 2ND INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM), 2015, : 1112 - 1115
  • [8] A cloud solution for multi-omics data integration
    Tordini, Fabio
    [J]. 2016 INT IEEE CONFERENCES ON UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING AND COMMUNICATIONS, CLOUD AND BIG DATA COMPUTING, INTERNET OF PEOPLE, AND SMART WORLD CONGRESS (UIC/ATC/SCALCOM/CBDCOM/IOP/SMARTWORLD), 2016, : 559 - 566
  • [9] An Optimized IoT-Enabled Big Data Analytics Architecture for Edge-Cloud Computing
    Babar, Muhammad
    Jan, Mian Ahmad
    He, Xiangjian
    Tariq, Muhammad Usman
    Mastorakis, Spyridon
    Alturki, Ryan
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (05) : 3995 - 4005
  • [10] Application of Big Data Analytics via Cloud Computing
    Yetis, Yunus
    Sara, Ruthvik Goud
    Erol, Berat A.
    Kaplan, Halid
    Akuzum, Abdurrahman
    Jamshidi, Mo
    [J]. 2016 WORLD AUTOMATION CONGRESS (WAC), 2016,