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Big Data Thinking and Its Biomedical Application

Petar Melih INAL, Nikhil Vishnu

Article ID: 859
Vol 2, Issue 1, , Article identifier:

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Big data thinking gradually rise with the coming era of big data. Big data characteristics could be summarized with 4V: volume, variety, velocity and value. The characteristics of big data thinking could be summed up in integrity, fault tolerance, correlation and intelligence. These characteristics were also the primary differences between big data thinking and small data thinking. The application of big data thinking in biomedical field became more and more widely, and the most commonly used was NCBI database. The process of mining valuable information in NCBI database was big data thinking. And the rise of Meta analysis and TCGA database would illustrate the huge application value of big data thinking in the biomedical field.


Big data; Big data thinking; Biomedicine

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Fang W, Zheng Y, Xiu J. Big data concept on key technologies and applications. Nanjing Xinxi Gongcheng Daxue Xuebao (Ziran Kexue Ban) Journal of Nanjing University of Information Science and Technology (Natural Science Edition) 2014; 6(5): 405-419.

Huang XR. The semantics, features and essence of big data. Changsha Ligong Daxue Xuebao (Shehui Kexue Ban) 2015; 30(6): 5-11.

Li JC. Big data and new mind on statistics. Tongji Yanjiu (Statistical Research) 2014; 31(1): 10-17.

Liu RT, Wang M, He HJ, et al. Hominid genomes and health. Jiyinzuxue Yu Yingyong Shengwuxue. (Genomics and Applied Biology) 2015; 34(6): 1333-1338.

Qiu XC. Bibliometric study of meta-analysis in medical research. Yixue Yanjiusheng Xuebao (J.Med.Postgra.) 2014; 27(7): 733-736.

Staff P. Dealing with data, challenges and opportunities, introduction. Science 2011; 331(6018): 692-693.

Vesset D, Woo B, Morris HD. Worldwide big data technology and services 2012-2015 forecast. IDC Report 2012; (1): 233485.

Wang K, Zhao RX, Yang SL, et al. DNA methylations associated with survival of lung adenocarcinoma with TCGA database. Nanjing Yike Daxue Xuebao (Acta Universitatis Medicinalis Nanjing) 2016; 36(6): 665-669.

Wang S, Li Z, Zheng CL, et al. Analysis of clinical significance of AKT3 expression in gastric cancer utilizing TCGA datasets. Zhongguo Yike Daxue Xuebao (Journal of China Medical University) 45(5): 398-401.

Weston AD, Hood L. Systems biology, proteomics, and the future of health care: Toward predictive, preventa-tive, and personalized medicine. Journal of Proteome Research 2004; 3(3): 179-196.

Zhang WM, Tang JY. Big data thinking. Zhihui Xinxi Xitong Yu Jishu (Command Information System and Technology) 2015; 6(2): 1-4.

Zhu JP, Zhang GJ, Liu XW. Clarity of a philosophy of data analysis during the age of big data. Tongji Yan jiu (Statistical Research) 2014; 31(2): 10-19.

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