Advertisement

Strategic planning for national biomedical big data infrastructure in China

Abstract

The promise that big data will revolutionize scientific discovery and technology innovation is now being widely recognized. With the explosive growth of biomedical data, life science is being transformed into a digital science in which novel insights are gained from in-depth data analysis and modeling. Extensive and innovative utilization of biomedical big data is a key to the success of precision medicine. Therefore, constructing a centralized national-level biomedical big data infrastructure becomes crucial and urgent for China. Such infrastructure should achieve superb capacity of safe data storage, standardized data processing and quality control, systematic data integration across multiple types, and in-depth data mining and effective data sharing. Full data chain service including information retrieval, knowledge discovery and technology support can be provided to data centers, research institutes and healthcare industries. Relying on Shanghai Institutes for Biological Sciences, agreements have been signed that a main node of the infrastructure will be located in Shanghai, and a backup node will be set up in Guizhou Province. After a construction period of five years, the infrastructure should greatly enhance China’s core competence in collection, interpretation and application of biomedical big data.

References

  1. 1.

    Mayer-Schönberger, V. and Cukier, K. (2013) Big Data: A Revolution That Will Transform How We Live, Work, and Think. Boston: Houghton Mifflin Harcourt

  2. 2.

    Chouard, T. (2016) The Go Files: AI computer wraps up 4-1 victory against human champion. Nature, doi: 10.1038/nature. 2016.19575.

  3. 3.

    Gray, J. (2009) Jim Gray on eScience: A Transformed Scientific Method. Hey, T., Tansley, S., and Tolle, K. M. eds. In The Fourth Paradigm: Data-intensive Scientific Discovery. Redmond, WA: Microsoft Research, xix

  4. 4.

    Hey, T., Tansley, S. and Tolle, K. M. (2009) The Fourth Paradigm: Data-intensive Scientific Discovery. Redmond, WA: Microsoft Research

  5. 5.

    Hood, L. and Rowen, L. (2013) The Human Genome Project: big science transforms biology and medicine. Genome Med., 5, 79

  6. 6.

    Stephens, Z. D., Lee, S. Y., Faghri, F., Campbell, R. H., Zhai, C., Efron, M. J., Iyer, R., Schatz, M. C., Sinha, S. and Robinson, G. E. (2015) Big data: astronomical or genomical? PLoS Biol., 13, e1002195.

  7. 7.

    Gomez-Cabrero, D., Abugessaisa, I., Maier, D., Teschendorff, A., Merkenschlager, M., Gisel, A., Ballestar, E., Bongcam-Rudloff, E., Conesa, A. and Tegnér, J. (2014) Data integration in the era of omics: current and future challenges. BMC Syst. Biol., 8, 11.

  8. 8.

    Ashley, E. A. (2016) Towards precision medicine. Nat. Rev. Genet., 17, 507–522.

  9. 9.

    Gligorijević, V., Malod-Dognin, N. and Pržulj, N. (2016) Integrative methods for analyzing big data in precision medicine. Proteomics, 16, 741–758.

  10. 10.

    Cochrane, G., Karsch-Mizrachi, I., Takagi, T. and the International Nucleotide Sequence Database Collaboration. (2016) The International Nucleotide Sequence Database Collaboration. Nucleic Acids Res., 44, D48–D50.

  11. 11.

    Wheeler, D. L., Barrett, T., Benson, D. A., Bryant, S. H., Canese, K., Chetvernin, V., Church, D. M., DiCuccio, M., Edgar, R., Federhen, S. (2016) Database resources of the national center for biotechnology information. Nucleic Acids Res., 44, D7–D19.

  12. 12.

    Zhan, Q. and Qian, H. (2016) Opportunities and Advantages for The Development of Precision Medicine in China. In Precision Medicine in China. Sanders, S. and Oberst, J. eds., pp. 6–9. Washington, DC: Science/AAAS

Download references

Acknowledgments

This work was supported by the National Key Research and Development Program on Precision Medicine (Nos. 2016YFC0901704, 2016YFC0901900 and 2016YFC0901600), the National Grand Program on Key Infectious Diseases (No. 2015ZX10004801-005), and the National High Technology Research and Development Program (Nos. 2015AA020104 and 2015AA020108).

Author information

Correspondence to Zefeng Wang or Yixue Li.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wang, Z., Wang, Z. & Li, Y. Strategic planning for national biomedical big data infrastructure in China. Quant Biol 5, 272–275 (2017). https://doi.org/10.1007/s40484-017-0114-5

Download citation

Keywords

  • biomedical big data
  • national infrastructure
  • precision medicine