资源描述：
1 Abstract The rapid growing comprehension and insight to genomic and human health data make it possible to prolong human life expectancy significantly in the next 20 years. The large scale implementation of personalized healthcare technology wil be the main driver of this change. Personalized health care services wil rapidly become popular with the dramatic drop in the price of genome sequencing services in three to five years. The vast majority of health and medical providers in the future wil begin to provide services based on user genomes and daily health data. The Gene Source Code Foundation is commited to build the worlds first storage and decentralized application plat for genomic and health data, the Gene Source Code System, with the expectation that a human healthcare data ecosystem wil be built around this and create one unique Economic Mechanism Encourage users to share genomic and health data within the ecosystem, provide researchers with adequate data support and provide data users with a friendly interface. The Gene Source Chain System wil create the worlds first distributed storage network blockchain system that provides genetic data and individual health data integrated interface. Health and medical service providers, including hospitals, chronic disease management agencies, and health consulting service providers, can use the gene source chain system to build DApps. These applications wil provide users with personalized, acurate health services based on genome and health data, subject to user consent. The Gene Source Chain team wil also create a DApp of smart health management asistant, which inspires users to share data and obtain health services, as a prove of concept application. For an individual user, he/she can receive Gene currency rewards while sharing health data, and can also obtain acurate health advice when his/her data is rich enough. The Gene Source Code Foundation believes that the human right to have a healthy life should be absolutely equal even in an era of exponential technology growth. This right should not be afected by the amount of wealth, simply because each one is already contributing to the health of al humankind. Gene Source Code system wil be based on trustful blockchain technology and data encryption/masking technology, so that each individual has ownership of health related data and the benefits within. 2 Table of Contents I Preface and Background 1.1 Technology Exponential Growth and Blockchain Technology Outbreak 1.2 The Rapid Development of Genomic and Healthcare Big Data 1.3 The Features of Current Genome Sequencing and Health Big Data II Industry Pain Points 2.1 Limited Ways to Access Genome and Healthcare Big Data 2.2 Scatered Healthcare and Medical Data in Private Companies and Hospitals is Dificult to Cross-examine and Utilize 2.3 The Systematic Storage of Genome and Health Big Data Also Presents Chalenges 2.4 People Have Poor Aces to Their Own Healthcare Data and Have Not Been Able to Obtain the Value of Their Own Data Collection III Blockchain Technology and New Oportunities 3.1 Blockchain Technology – the Disruptive Innovation 3.2 Blockchain Technology Drives Genomic Data Storage and Sharing 3 IV The Ecosystem of Gene Source Code System 4.1 The Constituent Units of Gene Source Code System 4.2 Interpretation of the Ecosystem V Blockchain Solutions Schema 5.1 Gene Source Code Architecture Design 5.2 Data Layer Architecture 5.3 Storage Layer Architecture 5.4 Incentive Layer Architecture 5.5 Application Layer Architecture 5.6 App - Personal Healthcare Companion VI Why We Can Do Beter 6.1 Team Introduction 6.2 Gene Source Code Team and Partners Have Rich BT IT Cross-border Experience 6.3 The Gene Source Code Project is Endorsed by Many Far-sighted Scientists in Famous Research Institute 6.4 Backing by Many Venture Capticals 6.5 Gene Source Code Foundation Philosophy and Goals 4 VII Gene Coin Development Programs VII The Use of Funds IX Gene Source Code Foundation Governance Mechanism X Gene Coin Roadmap XI Risk Warning and Disclaimer XII Customer Service, Contact and Support 5 I Preface and Background 1.1 Technology Exponential Growth and Blockchain Technology Outbreak The exponential growth of technology has profoundly and rapidly afected everyones lives in al fields, including the impact of skyrocketing growth in Blockchain technology. It has been nine years since Satoshi Nakamoto invented bitcoin in 2009. During this period, Blockchain technology has been greatly developed and consolidated. Digital cryptocurrency represented by bitcoin began to be gradualy understood, acepted and even sought by the people. Bitcoin that decentralizes digital virtual asets is more commonly known as digital gold, and its usage has also gradualy expanded from geeks to the general public. At the same time, there are many more exciting developments in the area of Blockchain cryptocurrency industry, such as the Ethereum Project, created by Vitalik Buterin and Gavin Wood in 2013, with great succes. Due to the ease of use of the Ethereum design concept, more and more decentralized applications, DApp Distributed Application, are built on the technology plat of Ethereum. In addition, there are a series of featured Blockchain projects such as Zcash, Dash, EOS and so on. The rapid development and evolution of blockchain technologies wil embrace the Blockchain application in various industries. 1.2 The Rapid Development of Genomic and Healthcare Big Data At the same time, in the field of health science, the rapid development of technology has also posed great opportunities and chalenges to mankind. In the foreseable future, mankind wil benefit from sharing big data on genes and human healthcare, wil greatly extend life spans and eliminate vast majority of diseases. As the price of genomic sequencing data has dropped rapidly, scientists and citizen scientists wil be free to aces vast amounts of genomic and human health data to 6 study and overcome specific medical and healthcare problems. As the price for gene sequencing is descending, scientists and citizen scientists can aford to aces vast amounts of genetic and body fitnes data for academic or medical purpose. Besides, research and cross study on DNA of other species on earth wil be beneficial as wel.. These studies wil make great progres for mankind in the fields of medicine, materials and energy. 1.3 The Features of Current Genome Sequencing and Health Big Data DNA sequencing s have been wel developed, from manual to capilary electrophoresis. The year 2001 is a milestone through the eforts of many countries, the HGP, human genome project has been completed, which took 13 years and cost 437 milion US dollars. At the beginning of the 21st century, with the advent of high-throughput sequencing technologies, both sequencing time and sequencing costs have been greatly reduced. By 2007, the birth of the first complete human genomic sequence map took only 1.5 milion U.S. dollars and three months. As technology continues to evolve, sequencing fluxes continue to grow. For example, Illuminas sequencer generates base pair data from one milion per day to bilions. And the cost of sequencing genome data reduced to les than 1,000 dollars. It can be predicted that with advances in technology, sequencing costs wil continue to decline, and we expect that the cost of a single genome wil fal to 100 in 3-5 years. 7 Nowadays, the development of the DTC Direct to Consumer industry makes the gene sequencing proces relatively easy. Most of the genome-level tests can be pered by noninvasively sample collection s, for example, extracting the DNA completely through oral cels saliva. And it can already met the quality criterion of the first generation and second generation sequencing. Although, the era of big data has came, the main focus is put on internet behavior and media data. As an increasing number of wearable fitnes devices enter the market and the Internet of things become popular, the focus on human big data analysis is aroused. When the fitnes big data era come, the human health and fitnes data wil grow exponentialy. It is widely acepted that collecting fitnes data is more valuable to human than traditional concerns can be. http/ 8 II Industry Pain Points 2.1 Limited Ways to Access Genome and Healthcare Big Data At present, there are stil many problems in the field of human genome research. The rapid development of human genome technology requires huge amounts of genome sample data and health related dataset, however, the available s to integrate those data are very limited. Large scale genomic and health data integrated applications are stil limited to scientific research fields. Moreover, scientists and researchers need to pay a big part of research funding to obtain data; these data sharing betwen subjects is quite limited; the majority of these data are only from the patients, just a few datasets from healthy people. 2.2 Scatered Healthcare and Medical Data in Private Companies and Hospitals is Dificult to Cross-examine and Utilize Although it is wel-known that genomic data can guide peoples healthy lifestyles, there is no incentive for the healthy population to take the initiative to obtain their own genomic data. Meanwhile, health related data such as rcise data, diet data, Medical record data and so on, are often pasively stored in various private enterprises, and there is almost no sharing of these valuable health data, and thus no possibility of related research. 9 Source Data Type Clinical Electrical record, Med record, etc. Health Check Blod glucose, blod presure, blod lipids, heart rate, height, weight, vision, etc. Behavioral Movement steps, use of electronic equipment, etc. Genetic Genome ination, family history, etc. Environmental Type of work, location of residence, pasive smoking, etc. Habitual Smoking, alcohol consumption, diet ingredients, etc. Basics Gender, age, etc. 2.3 The Systematic Storage of Genome and Health Big Data Also Presents Chalenges Due to the enormous volume of personal genome data, the existing storage and computation technologies are obviously chalenged the individuals original data volume can usualy reach 30G to 100G, while the traditional way of calculating the personal genome pipeline is about 2-3 days. Despite the current compresion algorithms and paralel procesing mechanisms for genomic data can acomplish this within hours, there is stil a great need for masive storage and computational efort while having large numbers of individual genome samples. There are stil lack of sample data in combination of human genome data and multi-dimension healthcare big data, since the current research institutes focus only on the combination of genome and tumor data. 2.4 People Have Poor Aces to Their Healthcare Data and Have Not Been Able to Obtain the Value of Their Own Data Collection People are constantly generating vast amount of data, of which health related data is a crucial part, and the sharing, aggregation, analysis, utilization and enormous value of these data wil have enormous added value, however the source of these data, the data 10 contributors were never involved in this proces nor shared the value of their own data. Therefore, the standardization and systematic storage of human genome and health big data is an urgent problem to be solved. In the future, there wil be many applications that can cal and integrate these data to provide personalized health advice to users. This proces is of great importance to the health of al human beings’ longevity and the elimination of the disease. III Blockchain Technology and New Oportunities 3.1 Blockchain Technology – the Disruptive Innovation Blockchain technology is based on decentralized network, combining the encryption algorithm, data scheme innovation and consensus mechanisms to ensure the consistency and continuity of distributed databases, enabling instant verification of data, traceability, anonymity, and failure Shielding, thus ing a set of eficient, economical, and secure of value-sharing system. Therefore, the equality, security and mas computing power of blockchain technology provides a completely new perspective for solving the problem of storing and sharing human genomic data. 3.2 Blockchain Technology Drives Genomic Data Storage and Sharing Encryption protocol and hashing mechanism ensure data encryption and transmision can be shield from the interference of third parties in any way, and also ensure limited aces to the users vital health data.The smart contract mechanism of blockchain technology wil provide individual users with the initiative to share their own genome and health data, Since blockchain technology can provide confidence and protect the fairnes of the incentive mechanism. 11 Decentralization of blockchain storage nodes wil provide a solid plat for researchers to have equal sharing of genomic and healthcare data. Decentralized storage nodes with blockchain technology also enable to a distributed networks to provide vast amounts of storage for genetic and healthcare data, with the capability to design consensus mechanism in a more secure manner. Based on the advantages of blockchain technology above, Gene Source Code Foundation wil build the worlds first distributed genetic storage system and set up an application plat based on genomic and healthcare data. We hope this system wil center on establishing a large scale health data utilization economic ecosystem. The mechanism can encourage users to share genomic and health data within the ecosystem, and the users can also get various health advices from the service providers. Those activities also provide researchers with adequate data for specific scientific research. Gene Source Code System wil build the first distributed storage system of gene and personal fitnes data. Health and medical care service provider, including hospitals, chronical disease management agency, health consulting services can develop DApp on gene sourcecode chain system. The applications can provide personalized precise service on the premise of users permision, given genomic and health data. 12 IV The Ecosystem of Gene Source Code System 4.1 The Constituent Units of Gene Source Code System Within this ecosystem, it wil consist mainly of the following abstract parties 1 Data Contributors 2 Data User 3 Storage Provider 4 Service Provider Gene Source Code Ecosystem Diagram 4.2 Interpretation of the
展开阅读全文