Release date: 2017-03-08 In the 2016 China “Top 100 Medical Healthcare†list published by the Arterial Network, the field of genetic testing has sprung up, with 18 companies listed, which are the most listed companies in the fields involved, including Huada Gene with RMB 20 billion. The market valuation ranks first. As the cost continues to decrease and the concept of genes becomes more and more popular, genetic testing companies are exploding in the medical and health industry with innovative genetic technologies. On the other hand, precision medicine was written into the “Thirteenth Five-Year Planâ€, and the NIPT pilot program was abolished. The favorable policy environment also provided a good soil for the growth of genetic testing companies. On the one hand, the increasing popularity of genetic testing, on the one hand, is the increasing production of data on a large scale. With such large-scale data, how to store, analyze and interpret this becomes the bottleneck and barrier that the industry must break through. Human genome-wide data is about 3 billion characters. In order to ensure the accuracy of interpretation, it is customary to read each character more than 30 times, equivalent to 100 billion characters. This is calculated, and without analyzing and interpreting, reading data is a great project. The genome-wide detection cycle of well-known genetic testing companies in China is 3 months, from sampling to sequencing, which takes one month, and the remaining two months are used in the analysis and interpretation of data. In 2017, global sequencing giant Illumina launched the NovaSeq sequencing series, which again set a new low for sequencing costs. This means that a large wave of data is approaching. How to find a more efficient data processing solution, how to improve the speed of data interpretation, will undoubtedly be the next topic in the industry. The arterial network (micro-signal: vcbeat) combed 42 companies involved in the analysis and interpretation of genetic data, and hoped to analyze the industry status from the perspective of the industry. Based on start-ups, no unicorns appear More than half of the 42 companies were established after 2010. Early establishments, such as Huada, Berry and Kang, and Huayinkang, have a relatively comprehensive business, so in the strict sense, there are no unicorns in this industry. Companies like Safford Gene, Huadian Cloud and Judao Technology, which are mainly engaged in data services, even start-ups with the core of biotechnology and information technology as human beings and the future are established in 2013. Before and after. Beginning in 2013, genetic data service related companies began to become active. Of course, the impact of the overall base of the entire genetic testing field during this period is not ruled out. However, in recent years, like Baimai, Annoyouda's enterprises with the core business of sequencing services have begun to expand into the data field, which seems to indicate the general trend of data analysis. At present, these corporate financing rounds are mainly concentrated in the Angel Wheel and the A round, and the scale is still relatively small. Twelve of the 42 companies are involved in business development, and seven of them are in the A round. Most of the B-round players in the market enter the market through business expansion. These enterprises are more representative of a market trend and cannot represent the maturity of enterprises in the market. Product Service: "Cloud Service" is the trend From the perspective of product distribution, traditional bioinformatics means still dominate, but cloud-based PAAS, SAAS and other cloud platforms are emerging. Undoubtedly, data computing, transmission and analysis on the cloud will save users a lot of hardware burdens, and at the same time, they can concentrate these aspects in one place, bringing users a more relaxed and efficient experience. Such a cloud experience is also being Become a trend in data processing. Traditional analysis is the most widely used Analytical software and systems are the most widely used products in the analysis process, and are more traditional methods of biological information analysis. The breadth of the analysis software is small and the operation is difficult. In contrast, data analysis systems are more diverse, and the breadth of application of data analysis systems of different complexity is different. A more comprehensive analysis system considers more from the IT architecture and analysis algorithm flow, and the difference between simple systems and software is not too great. This type of product has the largest density of enterprises, with a total of 27 companies. Representative companies include Berry and Kang, and Li Bing Technology. New and old players enter the market, "cloud service" is the future trend In addition to traditional IT tools, cloud-based computing and analytics platforms are also moving closer to genetic data. With a more lightweight storage solution and more efficient computing performance, the cloud platform plays an active role in data processing. 1PaaS: Building a cloud environment for the genetic field Compared with IaaS (Infrastructure as a Service) platform such as Alibaba Cloud, Baidu Cloud, Huawei Cloud, etc., the PaaS platform is more targeted and can provide more professional services for the characteristics of a certain field. The platform will build a cloud environment based on its own service area, which is convenient for companies in the segment to use as soon as possible. For the companies in the segmentation field, the emergence of the PaaS platform in the genetic field saves a lot of time and cost by eliminating the need to build a platform on its own. The PaaS platform for the genetic field started earlier in foreign countries, and the representative company Seven Bridge, DNAnexus, T Ute Genomic and so on. In recent years, domestic bioinformation cloud service providers have begun to go to market. Some of them are early-stage companies that have expanded their business, such as Huada and Baimaike. The other category is a startup like Cloud Technology, which is based on cloud services. The scale of the generation of genomic data is closely related to the cost of sequencing. The establishment time of these enterprises is basically consistent with the time point of the cost of sequencing. In 2013, Chen Chen, the former bio-information backbone of Huada University, resigned from the position of director of the Bioinformatics Office of the Institute of Infectious Diseases of the Chinese Center for Disease Control and Prevention, and founded Huadian Cloud, which specializes in clinical bioinformatics services. Huadian Cloud is deployed on the Huawei cloud platform and has accumulated more than 500 bioinformatics applications. It provides bioinformatics data analysis and reporting for clinical labs that lack the pain points of bioinformatics solutions. Different from China's point cloud, Judao Technology starts with data security, efficiency and ease of use, improves data transmission efficiency and software operation efficiency, and provides cloud computing resource scheduling services for biological companies that want to use cloud computing but do not know how to use them. . In 2014, a group of technical teams from Ali established the Gene Big Data Computing Service Platform. The platform provides an integrated solution for the transmission, storage, analysis, calculation and application of genetic data to serve the biological information cloud. At the same time, it provides an open interface that allows users to easily manage and manipulate data, and finally produces reports based on user needs. In addition, by using data compression technology to reduce the time and cost of transmission and storage, using distributed scheduling and execution engines to accelerate data analysis speed and throughput, the cloud service provided by the channel can not only help users to reduce hardware maintenance and update costs. It can also lower the cost threshold for data analysis. At the same time, based on such a cloud platform, many complex, locally unacceptable multi-sample analysis tasks are no longer subject to limited local data processing capabilities. On the one hand, the rise of these start-ups with cloud services as the core, on the other hand, the mid-stream or integrated business of the industry chain is also actively welcoming this cloud trend. In April 2015, with extensive experience in next-generation sequencing data analysis, BGI Online developed a cloud-based solution, BGI Online, to address the traditional challenges of analyzing, storing and sharing massive next-generation sequencing data. With a robust infrastructure and best-in-class security, BGI Online provides data storage, automated analytics, data transfer, biometric method development and sharing services for organizations of all types and sizes. The platform uses state-of-the-art resource management systems to ensure accurate allocation of resources while running computing tasks and real-time task monitoring, and timely feedback on possible errors. On such a platform, users can create their own analysis tools based on the open source software of Huada Gene. More importantly, the user's analysis tools can be combined with the BGI Online platform's public analysis tools, bioinformatics tools and other resources to create a complete set of analysis processes that better suit the user's own research needs. In February 2016, the BGI Online beta version was launched on Alibaba Cloud, the first large-scale bioinformatics analysis platform fully deployed on Alibaba Cloud. Relying on Alibaba Cloud's flexible storage and computing advantages, BGI Online can meet the needs of data processing, storage and transmission in different application scenarios and modes such as basic research, crop breeding and clinical applications, and also through the use of a series of advanced data technologies. Requirements for industry safety regulations such as the HIPAA Act. At the same time, the use of domestic servers to store and analyze sensitive genetic data is more in line with the norms of China's Human Genetic Resources Management Measures. The simple and easy-to-use interface and highly secure features allow doctors and researchers to hand over the tedious tasks of managing data and hardware maintenance to BGI Online and Alibaba Cloud to focus on the scientific and clinical issues they are trying to solve. This means that for research institutes, medical institutions, and small and medium-sized genetic industry startups, as long as they have genetic data, they do not have to build and maintain expensive and complex computing and storage platforms. BGI Online can decode the mysterious genes behind them. Mystery. The world's largest genomics research and development institution has opened the mysterious door to the genetics industry, making the genetic industry "at your fingertips." Of course, Huada is not the only company that is expanding its cloud business. In July 2015, Baimaike also launched Baimaike Cloud, a bio-big data information analysis platform tailored for researchers, to provide users with complete bioinformatics analysis and integrated public data solutions. In addition to mid-stream companies, some traditional bioinformatics companies, such as Lie Bing Technology and SMG Information, are also actively moving to the cloud. In addition, auxiliary software such as acceleration chips and data compression tools also play a supporting role in data processing. The role of this type of product is not to solve the problem, but how to solve this problem better. Such as more efficient calculations, faster and higher quality compression, and more. At present, there are relatively few enterprises involved in supporting software. Based on the own attributes of such products, it is unlikely that a full-time enterprise will be formed. 2SaaS: Cloud Analysis APP for Data Analysis The other is the SaaS (software as a service) platform. If the above PaaS platform is to build a cloud environment for genomics, then SaaS provides usable tools in this cloud environment. This is similar to the APP on the mobile phone. The service provider deploys the application software on its own server. The customer can order the required application software service to the service provider through the Internet according to their actual needs. According to the ordering service and the time and direction. The service provider pays the fee and gets the service through the internet. In 2015, Kevin Wellcome's cloud analysis service was officially launched, focusing on personal genome-wide data analysis. Based on Alibaba Cloud, Kiyun Wellcome is a SaaS service that provides faster, lower cost optimization services for genome-wide data. Also in 2015, the jellyfish gene focused on consumer-grade genes also launched the Health Management SaaS platform based on the cloud provided by Alibaba Cloud. Based on such a precise health management SaaS system, Jellyfish Gene has created a disease prevention and prevention system based on genetic data, creating a private health record for each client, collecting all data related to the customer's own health, such as medical history, eating habits. , genetic data, blood pressure, blood sugar, etc. Achieve disease prevention guided by genetic data and improve service quality for corporate customers. Qiyun Nord is focusing on the back-end computing services of gene sequencing companies, providing genetic testing companies with one-stop services for data storage, cloud computing, analysis, result reading and report generation. Help the testing company to quickly produce high-quality product reports. In addition, Qiyun Nord has also launched custom-made and R&D outsourcing services, and can also jointly develop products for genetic testing companies. In 2016, based on the advantages of Alibaba Cloud in batch computing and the large amount of biological samples and genetic data accumulated by Annoyouda since its establishment, the two companies jointly launched the “Big Ano Cloudâ€, a biological big data analysis cloud platform. It is hoped to realize rapid analysis and safe storage of high-throughput gene sequencing data, provide biological big data storage and management services, and integrate biological and clinical research data analysis services to promote the progress of precision medicine in China. The PAAS platform brings lightweight genetic data transmission and storage, which simplifies the process of genetic data analysis. The SaaS platform reduces the threshold for genetic data analysis, and is a group that has a need for bioinformatics analysis but does not know much about technology. Convenience is provided. In the past, data transmission was mainly achieved through network and hard disk transmission, which was not the best solution in terms of cycle and cost. The emergence of PaaS and SaaS cloud platforms, coupled with high-parallel tools such as cloud computing, is equivalent to the storage, transmission, analysis and calculation of data in the cloud, freeing the shackles of local processing, making the entire data processing process They are all smooth and brisk. Interestingly, whether it is PaaS platform or SaaS platform, most enterprises have chosen to cooperate with Alibaba Cloud as the cloud foundation built by their own platform. For example, Huada, Judao, and Jiyun Wellcome, Annoyun and so on. At present, there are 18 cloud players on the market, including 10 PaaS platforms and 8 SaaS platforms. Interpretation is the plateau Traditional biological information occupies half of the country, and the cloud platform is also spreading. In contrast, the interpretation link is slightly deserted. The interpretation link can be said to be the bottleneck in the bottleneck. Since most diseases are polygenic genetic diseases, which are controlled by multiple genes, different gene mutations, different mutation sites, and different types of mutations, these factors will affect the disease. The final phenotype. In addition, the genome contains a lot of information, and what is really understood by people is only about 2% of the total. The function of many genes is still unclear. In addition, the correspondence between genes and diseases has not yet been established. There are too many uncertainties in the interpretation process, and more needs to be judged manually. Even if there is a dream team like Suiyuan Gene, it is difficult to solve problems at the industry level. Whether it is scientific research or clinical, the interpretation of data has great limitations and challenges. Several companies, such as Saifu Gene, Shunyuan Gene and Kiyun Huikang, have proposed to productize their services and provide one-stop services from sequencing to interpretation. They hope to use their advantages in the interpretation process to make the interpretation of genetic data low. The same strategy is also adopted by Qiyun Nord and Anno Yunda's Anno cloud project, but the two companies are more inclined to all the services after the sequencing, and the genetic division is reduced through the clear division of sequencing and data analysis and interpretation. The industry threshold, while deeper mining of the value behind genetic data. At present, there are very few companies involved in this link, which can be said to be plateau. If there are more than 10 interpretation services and semi-automated interpretation tools and even text mining. There are only two of them that provide semi-automatic interpretation tools. Interpretation of the human liberation of the link, the database is the basis Then, as mentioned above, due to the complexity of the disease and the human understanding of the relationship between genes and diseases, the data interpretation process is subject to human factors. In fact, semi-automated data interpretation is not difficult to achieve, because the expert consensus guide does have a part that allows the machine to understand and automatically judge. The contradiction behind this is whether there is an industry-standard and really useful database. The current public disease database has different information standards, and most of the data contained are based on European and American studies. They are not fully applicable to specific races and lack the deep integration of genomics data and phenotypic data. At present, all genetic testing companies are doing one thing - data collection. By collecting and integrating public or private information, the company aggregates it into a database or a knowledge base after manual review. It is largely intended to correct a series of deviations in the current data interpretation by forming a large enough database of ordinary people. This is a valuable foundation work, but in countries that have developed rapidly in the field of genomics, such infrastructure work has been started long ago, such as the United Kingdom and the United States. In August 2015, Berry and Kang officially launched the “Shenzhou Genome Data Cloud†project, which was jointly built by Berry and Kanghe Alibaba Cloud to create a data cloud with a large number of Chinese population genome data as the core. Precise interpretation of genomic data. In September 2016, Berry and Kang announced the phased important achievements of the “Shenzhou Gene Data Cloud†project, completed the construction of the world's first Chinese population genome database, and filled the gap in the international genetic database lacking the unique genomic data information of the Chinese population. In September 2016, the National Gene Bank of Shenzhen University was officially opened. This is the only national gene bank approved in China. The gene bank's database, sample library, living library, and planning data capabilities all surpass the international three major gene data centers, and its comprehensive ability ranks first in the world, becoming China's first national genetic data center. In addition, a number of midstream testing companies are preparing for the preparation of the gene bank. In July 2015, Haipulos and Shenzhen People's Hospital launched and launched a “10,000 Cancer Gene Sequencing Programâ€. It is reported that more than 30 top hospitals or departments in the country have joined the “10,000 Cancer Gene Sequencing Program†and have completed genetic testing of nearly 5,000 patients with cancer or high-risk groups. In July 2016, led by Jinan University, the first Asian reference genome “Huaxia No.1â€, which was completed by the future group, was published online in Nature Communications. The study is led by Jinan University, from the University of Southern California, the University of Washington, the Ohio State University, the National Institutes of Health Biotechnology Information Center, Wuhan Institute of Biotechnology, Future Group, Columbia University, Baylor College of Medicine, Cold Spring Harbor Laboratory A number of scientific research units have worked together to complete. The release of “Huaxia No.1†indicates that the domestic research team has entered the forefront of the world in the field of third-generation sequencing, and has filled the gap in the lack of fine reference genomes in disease research in the Chinese population. As gene sequencing becomes one of the main contents of the national health medical big data strategy, “Huaxia No.1†will become an important basic work to promote the application of clinical and scientific big data, and vigorously promote the development of genetic disease research and diagnosis in China. In fact, almost all mid-stream sequencing companies are currently collecting genomics data, but for companies to form a gene database of sufficient size, it will take time to brew. In addition, after the data scale reaches a certain level, whether the enterprise will share, directly affects whether the database is widely used, which may require a government-level layout. Conclusion: Database is the foundation, cloud analysis becomes the trend At the macro level, most companies are still start-up companies before the A or A round. It can be said that the market is still in the gestation stage. And more mature companies like Mingmu, Baimaike, and Anuoyouda have entered the market, and it seems to represent the industry trend (especially the cloud platform). From the perspective of product distribution, there are many enterprises based on the traditional analysis methods of analysis software and analysis system, but in the face of the soaring data scale, these methods are difficult to achieve absolute breakthrough. The cloud technology means such as PaaS and SaaS greatly reduce the load of the data processing link by transferring the data analysis process to the cloud (whether it is the physical weight on the hardware or the psychological load on the processing speed). However, most of these products are focused on data analysis. Because most human diseases are the result of the joint action of multiple genes, they involve the expression of variables of multiple genes. The interpretation of these data must take into account multiple variables of multiple genes, so there must be a strong and available database support behind this link. On this basis, it is perhaps a feasible solution to use technology to find an automated, alternative artificial channel to save time and cost. In the National Development and Reform Commission officially issued the "13th Five-Year" Bio-Industry Development Plan, many popular concepts such as genetic testing, cell therapy, immunotherapy, gene editing, and prenatal screening were "named". The “Planning†mentioned in the development goals that the ability to detect genes (including pre-pregnancy, prenatal, and neonatal) covers more than 50% of the birth population. With the pre-natal testing of Dongfeng, the concept of genetic testing will be recognized and accepted by a wider range of people, coupled with continued breakthroughs in cost control, and may be expected to be universal in the future. Whether it is non-invasive prenatal or tumor detection, or genome-wide detection, data analysis and interpretation will be accompanied by the whole process, the popularity of sequencing is bound to drive the development of data processing. Faced with the torrent of data approaching step by step, a data war is about to start. Source: Arterial Network Diaphragm Valve,Stainless Steel Diaphragm Valve,Hygienic Diaphragm Valve,Stainless Steel Mix Valve Wenzhou Gaoya Light Industry Machinery Co.,ltd. , https://www.hongyafitting.com