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efficient, and accurate analytical models and theoretical systems for bio-medicine
applications, the essential governing mechanism behind complex biological phe-
nomena may be revealed. Not only the future development of bio-medicine can be
determined, but also the leading roles can be assumed in the development of a series
of important strategic industries related to the national economy, people's livelihood,
and national security, with important applications such as medical care, new drug
R&D, and grain production (e.g., transgenic crops).
The completion of HGP (Human Genome Project) and the continued devel-
opment of sequencing technology also lead to widespread applications of big
data in the field. The masses of data generated by gene sequencing go through
specialized analysis according to different application demands, to combine it with
the clinical gene diagnosis and provide valuable information for early diagnosis and
personalized treatment of disease. One sequencing of human gene may generate
100-600 GB raw data. In the China National Genebank in Shenzhen, there are 1.3
million samples including 1.15 million human samples and 150,000 animal, plant,
and microorganism samples. By the end of 2013, 10 million traceable biological
samples will be stored, and by the end of 2015, this figure will reach 30 million.
It is predictable that, with the development of bio-medicine technologies, gene
sequencing will become faster and more convenient, and thus making big data of
bio-medicine continuously grow beyond all doubt.
In addition, data generated from clinical medical care and medical R&D also
rise quickly. For example, the University of Pittsburgh Medical Center (UPMC)
has stored 2TB such data. Explorys, an American company, provides platforms
to collocate clinical data, operation and maintenance data, and financial data. At
present, about 13 million people's information have been collocated, with 44 articles
of data at the scale of about 60TB, which will reach 70TB in 2013. Practice Fusion,
another American company, manages electronic medical records of about 200,000
patients.
Apart from such small and medium-sized enterprises, other well-known IT
companies, such as Google, Microsoft, and IBM have invested extensively in
the research and computational analysis of methods related to high-throughput
biological big data, for shares in the huge market as known as the “Next Internet."
IBM forecasts, in the 2013 Strategy Conference, that with the sharp increase of
medical images and electronic medical records, medical professionals may utilize
big data to extract useful clinical information from masses of data to obtain a
medical history and forecast treatment effects, thus improving patient care and
reduce cost. It is anticipated that, by 2015, the average data volume of every hospital
will increase from 167TB to 665TB.
3.1.5
Data Generation from Other Fields
As scientific applications are increasing, the scale of datasets is gradually expand-
ing, and the development of some disciplines greatly relies on the analysis of masses
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