Where is the way out of the bio-medical big data?

In the past World Cup, there is no octopus Paul, no King Bailey, fans are how to ensure that the game forecast to seize the winning machine?—— worthy of thousands of fans fortunately, big Data met the World Cup. Relying on the scientific algorithm data analysis, Baidu, Goldman Sachs, Google, Microsoft constitute the World Cup "crazy guessing ball" match lineup, various "bizarre" results came out, the small partners again and again stunned kneel in these carrier software based on the large data of God forecast. Nowadays, big data is pouring into all walks of life, and there is a growing trend.

In fact, the concept of large data is not new, data processing from the birth of the time has been, the Ancients Knot Chronicle is the basic statistics, the statistics themselves ate a few meals dozen times to hunt .... More recently, the Data Warehouse has matured for decades before the word "Big Data" appeared. Recently, large data are profoundly affecting various business changes, including agriculture, finance, medical and other fields. Large data has become one of the hottest concepts at the moment. However, how to use the existing IT technology to analyze large data efficiently is still the primary problem in the field of large data management application.

What is the situation of large data application in biomedical field? What's the way out of the big data for biomedical medicine? Where's the road?

Bio-medical data is generally very "heavy"

Large data is considered a key node in changing the industry. With the rapid development of biotechnology and medical technology and the maturation of high-throughput means, large data of biomedical industry have been rapidly expanding. However, unlike other industries, data in the biomedical industry are fragmented, fragmented, low in transparency, and have such characteristics as interpretation. The more prominent is that the biomedical industry data is generally very "heavy", and has a light and easy to resolve the characteristics of other industry data is clearly distinguished, showing a huge amount of information, different analytical strategies may come to rich results and other characteristics.

Due to these characteristics of the large data in the biomedical field, the calculation is often complicated, and the traditional biomedical computing relies on the manual environment Department to lead to time-consuming and inefficient. At the same time, traditional IT services from equipment procurement to installation and commissioning, it will take months, it is difficult to timely response to business changes. With the rapid growth of biomedical biomedical industry data and long-term preservation of historical data, it has gradually become a big burden for enterprises because of the increasing cost of investment and maintenance. It technology has become a stumbling block to the development of biomedical medicine in the age of large data.

Bio-Medical Large data outlet--cloud computing

Cloud computing can be a winning weapon in the biomedical field to conquer big data it checkpoints. Cloud computing platform can provide users with a large amount of flexible computing, storage resources, applicable to the biomedical industry business large-scale computing processing, to help users quickly deploy and manage large-scale and scalable IT infrastructure resources. By virtue of security, rapid and other characteristics of the current biological medical data development is the only way out.

At this stage, what new requirements should be met by cloud computing platform to support the rapid management and analysis of large data? How to consider the large data requirement in the planning of the cloud platform by enterprises?—— These have become the problem that the biological medical enterprise needs to solve at present. At the upcoming 2014 Bio-medical Data Summit Forum, Mr. Zhang Zhenlen, a technical director from VMware's Greater China region, will discuss these hot issues with you in depth. By then, Zhang Zhenlen will focus on "big data on cloud computing platform Requirements", "How to better serve the big data through cloud computing" and other issues to illustrate the best combination of large data and cloud computing platform, to explore the possibility of cloud computing for the advancement of biomedical technology to provide maximum support.

In addition, the 2014 Bio-Medical Data Summit Forum will be large data collection and analysis of medical norms, "end-cloud-end" processing, as well as medical data in the clinical application of the significance of a comprehensive interpretation of the relevant experts and industry leaders to build the top platform for communication.

Biological medical data way--disease prevention and Health management

Disease prevention and health management or will become one of the important path of biomedical large data. With the rapid development of nucleic acid sequencing technology, genomic data accumulation speed unprecedented, but also for us to fully tap and use genomic data to provide a large number of information sources, the use of these large numbers of researchers can paint a clear health spectrum, to achieve human health proactive prevention and management. Internet technology will also promote the management and application of health data, such as, the Google team based on People's Daily search terms aggregated large data have achieved more accurate prediction of seasonal influenza epidemic, and provide users with the basic search terms of the data for the researchers to use other similar research.

The participation of large data will have a great impact on the prevention and health management model of communicable diseases. On the basis of mass data generation, researcher Yang Ruifu that the development of Internet technology and the transition from Central hospital to family in the new century will promote the change of human disease prevention and Health management model. "The perfect combination of large data, internet and new family health care technologies will make a positive contribution to human health management." ”