Big data is getting more and more attention. Many universities in Europe and America have set up data science research institutions and offered data science courses. Nature and Science also published special issues on big data in 2008 and 20 1 1 respectively to discuss the challenges brought by big data. As one of the most active scientific research fields, big data in the biomedical field has also attracted much attention.
Sources of biomedical big data: The following factors promote the generation of biomedical big data.
The wholeness of life and the complexity of disease. For example, chronic diseases that seriously threaten human health are mostly complex diseases, and their occurrence has complex genetic and molecular mechanisms. Influenced by genes, environment and their interaction, its etiology research will produce a lot of data.
Development of quantitative technology and reduction of genome sequencing cost in Qualcomm. High-throughput sequencing technology can sequence millions of DNA at the same time, which makes it possible to analyze the transcriptome and genome of a species in detail. With the completion of the human genome project and the rapid development of computing power, the sequencing cost of each genome has been reduced from millions of dollars to thousands of dollars (and will continue to decrease).
Hospital informatization and the rapid development of IT industry. The human body itself is an important source of biomedical big data. With the rapid development of hospital informatization and IT industry, more and more human data can be stored and utilized. For example, X-ray, 3D nuclear magnetic resonance, mammography and 3DCT scanning include 30M, 150M, 120M and 1G respectively. By 20 15, every hospital in the United States will need to manage 665T of data.
Biomedical big data covers a wide range of fields related to human health: clinical medicine, public health, medical research and development, medical market and cost, individual behavior and emotion, human genetics and genomics, social demography, environment, health network and media data.