WO2023101272A1 - Système de gestion intégré pour générer, faire circuler et échanger des jnf en fonction de données génomiques et procédé associé - Google Patents

Système de gestion intégré pour générer, faire circuler et échanger des jnf en fonction de données génomiques et procédé associé Download PDF

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WO2023101272A1
WO2023101272A1 PCT/KR2022/018152 KR2022018152W WO2023101272A1 WO 2023101272 A1 WO2023101272 A1 WO 2023101272A1 KR 2022018152 W KR2022018152 W KR 2022018152W WO 2023101272 A1 WO2023101272 A1 WO 2023101272A1
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nft
image
genome data
rgb
bio
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Korean (ko)
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박종화
조수안
변하나
전성원
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주식회사 클리노믹스
울산과학기술원
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Publication of WO2023101272A1 publication Critical patent/WO2023101272A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/04—Payment circuits
    • G06Q20/06—Private payment circuits, e.g. involving electronic currency used among participants of a common payment scheme
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B45/00—ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B99/00—Subject matter not provided for in other groups of this subclass

Definitions

  • An embodiment of the present invention relates to an integrated management system and method for generating, distributing, and trading NFTs based on genomic data.
  • NFT stands for 'non-fungible token' and means 'non-fungible token' or 'non-fungible token'. In other words, NFTs are assets that are unique and cannot be replaced or copied without permission.
  • NFTs are characterized by ensuring their uniqueness by permanently leaving encrypted transaction details on the blockchain.
  • NFTs can also be said to be digital assets with inherent value, and have the advantage that counterfeiting and tampering are impossible because the source of the original is clearly included using metadata.
  • NFTs Digital paintings or music are prime examples of digital assets that can be turned into NFTs (supporting various formats such as JPG, GIF, MP3, GLB, MP4, etc.).
  • the NFT market is currently art, collectibles, metaverse, sports, games, and utilities. According to the information disclosed in , it is as shown in FIG. 1 .
  • Genomic (genetic) information is the most accurate and precise digital information that defines a human being.
  • the definition of genomic information goes beyond DNA and is linked to various multiomics of an individual or group, and information that can be expressed as genome (gene) information includes each individual or animal (dog, cat, bird, etc.) ) and exogenous genomes (epigenomes), transcripts, proteomes, metabolomes, and clinical information of plants.
  • genome information can be said to be the starting point of individual uniqueness in that it does not change forever once it is determined, such as the date and time of birth of a child.
  • Transcripts derived from genomic information also hardly change, but their function and utility are determined by their expression level. Thus, transcripts from an individual's point of time or within the environment can also be included as part of digital genomic information.
  • Exogenous (epigenome) information is derived from genomic information, but is information that can change over a certain period of time or over age and health status.
  • Proteome refers to protein sequence information in which genomic information is transcribed and translated again.
  • Protein structure refers to three-dimensional protein coordinate information determined by protein sequences, and this may also be included in a kind of genome data determined by individual genome information.
  • Patent Publication No. 10-2009-0082553 published date: July 31, 2009
  • Patent Registration No. 10-2040509 registration date: October 30, 2019
  • An embodiment of the present invention is an individual's unique information derived from genomic or genetic information for various living organisms such as animals and plants, and genomic information (exogenome (epigenome), transcriptome, proteome, metabolite, clinical information, etc.) All information is NFTized, and NFT information is secured based on the genome or genetic information of individuals and the genome or genetic information of pets or plants by using the core algorithms and programs necessary for the transaction, distribution, and production of NFT information. It provides a platform that can be distributed and traded online, fast, uniquely traceable, and managed to have its own authority.
  • An integrated management system for generating, distributing, and trading NFTs based on genomic data generates bio-arts images by converting genotype information included in genomic data into color information to generate bio-arts images. wealth; an NFT generation management unit that converts the bio-arts image into an NFT image and stores and manages it; And an online NFT market unit for mediating online transactions for the NFT image.
  • the bio-arts image generation unit includes an RGB hexadecimal code conversion unit that converts at least one genotype information of the genome sequence information and mutation information of the genome data into RGB hexa code that can be expressed in RGB colors; and generating a unique image based on a hexa code by converting the RGB hexa code converted through the RGB hexa code conversion unit into a two-dimensional figure composed of RGB colors, a gene including at least one gene characteristic test result for the genome data
  • a unique image generating unit providing the unique image as the bio-arts image when a prediction report does not exist may be included.
  • the RGB hexacode conversion unit may convert the genome data into the RGB hexacode based on predefined RGB hexacode conversion information in which a combination of one RGB hexacode and a plurality of genotype information corresponds to each other.
  • the bio-arts image generation unit analyzes the gene characteristics of the gene prediction report when the gene prediction report exists according to the request of the genome data provider who provided the genome data, and the gene characteristics provided as the analysis result.
  • a gene group specification unit for specifying a gene group as one of a plurality of pre-categorized gene groups; a gene group image conversion unit which presets image sources for each gene group and converts the gene group specified through the gene group specification unit into a preset image source; and an artificial intelligence image combination unit generating the bio-arts image by combining the unique image and the image source through a predefined artificial intelligence random algorithm.
  • the NFT generation management unit may further include: an NFT conversion unit that converts the Bio-Arts image into the NFT image and generates an encryption key and a decryption key upon conversion of the NFT image; An NFT storage management unit for storing the NFT image, the encryption key, and the decryption key generated through the NFT image conversion unit on a blockchain network; and an NFT provider that delivers the NFT image stored on the blockchain network, the encryption key, and the decryption key to an NFT buyer when the transaction of the NFT image is completed through the online NFT market unit.
  • the online NFT market unit NFT transaction application unit for providing basic information of the provider of the NFT image and corresponding genome data, and applying for at least one online transaction of license transaction and ownership transaction of the NFT image; And an encryption key for processing NFT payment using cryptocurrency according to the transaction request of the NFT transaction application unit, and confirming the NFT image requested through the NFT transaction application unit and genome data matched with the corresponding NFT image when payment is completed.
  • it may include an NFT payment processing unit that provides the decryption key to the NFT buyer.
  • the bio-arts image generator converts genotype information included in genome data into color information to generate bio-arts images.
  • a bio-arts image generating step an NFT creation and management step of converting the bio-arts image into an NFT image and storing and managing it, by an NFT creation management unit; and an online NFT transaction mediation step in which an online NFT market unit mediates an online transaction for the NFT image.
  • the bio-arts image generating step may include converting at least one genotype information of the genome sequence information and mutation information of the genome data into RGB hexa code that can be expressed in RGB color; And converting the RGB hexacode converted through the RGB hexacode conversion step into a two-dimensional figure composed of RGB colors to generate a unique image based on the hexacode, including at least one genetic characteristic test result for the genome data
  • a unique image generating step of providing the unique image as the bio-arts image when the gene prediction report does not exist may be included.
  • a combination of one RGB hexacode and a plurality of genotype information corresponds to each other to convert the genome data into the hexacode based on predefined RGB hexacode conversion information.
  • the bio-arts image generating step if the gene prediction report exists according to the request of the genome data provider who provided the genome data, the gene characteristics of the gene prediction report are analyzed, and the gene provided as the result of the analysis
  • the NFT generation and management step may include: an NFT conversion step of converting the Bio-Arts image into the NFT image and generating an encryption key and a decryption key upon conversion of the NFT image; An NFT storage management step of storing the NFT image, the encryption key, and the decryption key generated through the NFT conversion step on a blockchain network; and an NFT providing step of delivering the NFT image stored on the blockchain network, the encryption key, and the decryption key to an NFT buyer when the transaction of the NFT image is completed through the online NFT transaction step.
  • the online NFT transaction step NFT transaction application step of providing basic information of the NFT image and corresponding genome data provider, and applying for at least one online transaction of a license transaction and ownership transaction of the NFT image; And processing the NFT payment using cryptocurrency according to the transaction request in the NFT transaction request step, and confirming the NFT image requested through the NFT transaction request step and genome data matched with the corresponding NFT image when payment is completed
  • An NFT payment processing step of providing an encryption key and a decryption key to the NFT buyer may be included.
  • all information unique to an individual derived from genomic or genetic information on various living organisms such as animals and plants, and genomic information (exogenome (epigenome), transcriptome, proteome, metabolite, clinical information, etc.) NFT and use the core algorithms and programs necessary for the transaction, distribution, and production of NFT information to secure NFT information based on the genome or genetic information of individuals and the genome or genetic information of pets or plants, It can provide a platform that can be distributed and traded online that is fast, uniquely traceable, and managed to have its own authority.
  • Figure 1 is a graph showing the market distribution based on the market distribution and the number of transactions based on the sales scale provided by The world's largest NFT data resource.
  • FIGS. 2 and 3 are block diagrams shown to explain the overall operational flow of the integrated management system for generating, distributing, and trading NFTs based on genomic data according to an embodiment of the present invention.
  • FIG. 4 is a diagram showing the overall configuration of an integrated management system for generating, distributing, and trading NFTs based on genomic data according to an embodiment of the present invention.
  • FIG. 5 is a block diagram showing the configuration of a bio-arts image generating unit according to an embodiment of the present invention.
  • FIG. 6 is a diagram shown to explain a RGB hexadecimal code conversion process based on genome data according to an embodiment of the present invention.
  • FIG. 7 is a diagram for explaining a process of generating an image source based on a gene prediction report according to an embodiment of the present invention.
  • FIG. 8 is a diagram illustrating a process of generating a bio-arts image by combining a unique image based on RGB hexadecimal code and an image source based on a gene prediction report through an artificial intelligence random algorithm according to an embodiment of the present invention.
  • FIG. 9 is a block diagram showing the configuration of an NFT generation management unit according to an embodiment of the present invention.
  • FIG. 10 is a diagram illustrating a process of generating an NFT image obtained by performing NFT conversion on a Bio-Arts image according to an embodiment of the present invention.
  • FIG. 11 is a block diagram showing the configuration of an online NFT market unit according to an embodiment of the present invention.
  • 12 and 13 are diagrams shown to explain a blockchain work pipeline of an online NFT market unit according to an embodiment of the present invention.
  • FIG. 14 is a diagram showing the types and characteristics of cryptocurrency that can be used in the online NFT market unit according to an embodiment of the present invention.
  • 15 is a flowchart showing the entire process of an integrated management method for generating, distributing, and trading NFTs based on genomic data according to another embodiment of the present invention.
  • 16 is a flowchart illustrating a step of generating a bio-arts image according to another embodiment of the present invention.
  • 17 is a flowchart illustrating NFT generation management steps according to another embodiment of the present invention.
  • FIG. 18 is a flowchart illustrating an online NFT transaction step according to an embodiment of the present invention.
  • biomedical data based on the genome or genes of all living things are only one. It is unique data that does not exist, and after converting it into a unique digital form that cannot be replaced, it is traded and distributed, and through this, profit is obtained, desired health information is obtained, and the value of all various living things such as animals and plants is determined and distributed. And it is about a safe and secure system that can make transactions, and it is possible to solve the absence of a system in which humans turn all unique information related to themselves and surrounding creatures into NFT, a form of guaranteed information online. .
  • Genome, gene, or medical information is a very important task to understand by converting concepts with great expertise into intuitively easy-to-understand images (bio-arts), and to sell and utilize the images.
  • FIGS. 2 and 3 are diagrams shown to explain the overall operational flow of the integrated management system for generating, distributing, and trading NFTs based on genomic data according to an embodiment of the present invention.
  • the integrated management system 1000 for generating, distributing, and trading genomic data-based NFTs allows individuals (genomic data providers) to use genomic data in a single form or in a mixed form.
  • the form DNA + RNA
  • the uploaded genome data is converted into a unique image through an artificial intelligence algorithm-based analysis process and provided.
  • the portal site creates a unique genome data image as another unique art image through an automated image generation algorithm, converts it into NFT, and stores it on the server of the portal site.
  • the NFT image may be combined with the encrypted genome data after encoding the corresponding genome data and stored on the blockchain network.
  • a gene prediction report can be generated through analysis of uploaded genome data and stored like genome data in an NFT image.
  • NFT images containing genome data can be distributed and traded using cryptocurrency or cryptocurrency within the marketplace within the portal.
  • the method of selling NFT ownership and usage rights is applied to the NFT transaction method, and even the data (genome data, gene prediction report analysis results) included in the NFT image can be handed over during the transaction.
  • genetic prediction reports can also be NFTed, distributed, and traded to provide not only primitive genomic data but also standardized genetic characteristic data of individuals through the marketplace within the portal.
  • NFT consumers purchases are expected to be research institutes, hospitals, companies, etc. that require data (genome data, gene prediction report analysis results), but are not limited thereto, and can be traded to all consumers who need the data. .
  • a block-chain identity authentication system can be installed to limit the distribution and trading of NFTs only to consumers whose identities have been verified.
  • FIG. 4 is a block diagram showing the entire configuration of an integrated management system for generating, distributing, and trading NFTs based on genomic data according to an embodiment of the present invention
  • FIG. 5 is a bio-arts image according to an embodiment of the present invention. It is a block diagram showing the configuration of the generation unit
  • FIG. 6 is a diagram for explaining the RGB hexadecimal code conversion process based on genome data according to an embodiment of the present invention
  • FIG. 7 is a diagram according to an embodiment of the present invention. It is a diagram shown to explain the process of generating an image source based on a gene prediction report, and FIG.
  • FIG. 8 is a unique image based on RGB hexadecimal code and an image based on a gene prediction report through an artificial intelligence random algorithm according to an embodiment of the present invention. It is a diagram showing a process of generating a bio-arts image by combining sources, FIG. 9 is a block diagram showing the configuration of an NFT generation management unit according to an embodiment of the present invention, and FIG. 10 is a block diagram according to an embodiment of the present invention. It is a diagram showing a process of generating an NFT image obtained by performing NFT conversion on a bio-arts image, and FIG. 11 is a block diagram showing the configuration of an online NFT market unit according to an embodiment of the present invention.
  • FIG. 14 shows the types and characteristics of cryptocurrency that can be used in the online NFT market unit according to an embodiment of the present invention. is the drawing shown.
  • an integrated management system 1000 for generating, distributing, and trading NFTs based on genome data includes a bio-arts image generator 100, an NFT generation management unit 200, and At least one of the online NFT market unit 300 may be included.
  • the bio-arts image generator 100 receives genome data uploaded from a genome data provider (individual) through a portal site operated by the integrated management system 1000 for NFT generation and distribution, and inputs the uploaded genome data.
  • Geno-Eye Algorithm Geno-Eye Algorithm
  • Genotype information included in genome data can include transcriptome, proteome, clinical information, etc.
  • -Arts images Bio-Arts Image
  • the Geno-Eye algorithm means a processor for generating a unique mark that is the signature of the algorithm and contains actual genome sequence information and cannot be imitated by anyone, and creates a new genre of artistic image and corresponding It can play a role in breathing life into an image.
  • the genome data may be data of 100 MB or less parsed by the Geno-Eye algorithm, but the data capacity of the genome data is not limited.
  • the bio-arts image generator 100 includes an RGB hexacode converter 110, a unique image generator 120, a gene group specification unit 130, and a gene group image converter 140 and at least one of the artificial intelligence image combination unit 150 may be included.
  • the RGB hexacode conversion unit 110 converts at least one genotype information of genome sequence information and mutation information of genome data into RGB hexacode that can be expressed in RGB color. It can (1, 2).
  • the RGB hexacode conversion unit 110 may convert the corresponding genome data into RGB hexacode based on predefined RGB hexacode conversion information in which a combination of one hexacode and a plurality of genotype information corresponds to each other.
  • Each genotype information combination of genome data is converted into a corresponding RGB hexadecimal code, and the converted RGB hexadecimal code can be designed to be expressed in a color composed of corresponding RGB.
  • the result of converting the genome data into RGB hexa code may vary depending on the characteristics and size of the input genome data.
  • the unique image generation unit 120 may generate a unique image based on RGB hexadecimal codes by converting the RGB hexadecimal code converted through the RGB hexadecimal code conversion unit 110 into a two-dimensional figure composed of RGB colors.
  • the RGB hexacode based on genome data is expressed as a band or block (role of skeleton) composed of RGB colors, and the process of attaching flesh to the skeleton by arranging colors according to the designed band or block can proceed (3).
  • the unique image generation unit 120 may provide a unique image as a bio-arts image when there is no gene prediction report including at least one genetic characteristic test result for genome data.
  • the gene prediction report can be omitted if the genome data provider has not selected or does not want to, so if the gene prediction report does not exist, a unique image can be applied as a bio-arts image.
  • the gene group specification unit 130 analyzes the gene characteristics of the gene prediction report when there is a gene prediction report according to the request of the genome data provider who provided the genome data, and displays the gene characteristics provided as a result of the analysis in advance. It can be specified as any one group among a plurality of categorized gene groups. For example, as shown in FIG. 7, if a genome data provider wants to be provided with a gene prediction report, the gene characteristics of the provider are analyzed (1), and based on this, disease information, physical characteristics information, and disease risk are analyzed. The analysis result of information, etc. can be compared with predefined category information to be identified as a gene group of a specific category (2).
  • the gene group image conversion unit 140 may convert the gene group specified through the gene group specification unit 130 into a preset image source since image sources are preset for each gene group. For example, as shown in FIG. 7, when it is specified as gene group 2, find a preset image source for gene group 2, match the image source with gene group 2, and provide an image source for gene group 2. By doing so, the individual's genetic prediction report can finally be converted into an image source.
  • the artificial intelligence image combination unit 150 combines a unique image and an image source through a predefined artificial intelligence random algorithm to create a bio-arts image. can create As shown in FIG. 8, the unique image is an image based on RGB hexadecimal code generated using genome data, and the image source is an image generated based on a gene prediction report.
  • the artificial intelligence random algorithm can generate a unique Bio-Arts Image by receiving these two images and performing random color combination operations.
  • the NFT generation management unit 200 may convert and store and manage the bio-arts image generated through the bio-arts image generation unit 100 into an NFT image.
  • the NFT generation management unit 200 may include at least one of an NFT conversion unit 210, an NFT storage management unit 220, and an NFT providing unit 230, as shown in FIG.
  • the NFT conversion unit 210 may convert a Bio-Arts image into an NFT image, and generate an encryption key and a decryption key when converting the NFT image. Since NFT image conversion can be performed using a known NFT image conversion algorithm, a detailed description thereof will be omitted. However, when converting NFT images, genome data or information on genome data and gene prediction reports may also be encrypted, and at this time, an encryption key and a decryption key may also be generated.
  • the NFT storage management unit 220 may store the NFT image, encryption key, and decryption key generated through the NFT image conversion unit 210 on a blockchain network, and use the corresponding data through blockchain identity authentication .
  • the NFT provider 230 may deliver the NFT image stored on the blockchain network, the encryption key, and the decryption key to the NFT buyer when the NFT image transaction is completed through the online NFT market unit 300.
  • the online NFT market unit 300 may mediate online transactions for NFT images.
  • the online NFT market unit 300 may include at least one of an NFT transaction application unit 310 and an NFT payment processing unit 320, as shown in FIG.
  • the NFT transaction application unit 310 provides basic information (gender, age, occupation, etc.) of the provider of the NFT image and corresponding genome data, and may apply for at least one online transaction of license transaction and ownership transaction of the NFT image. .
  • the transaction (sale) of the NFT license means an online transaction method in which the genome data provider takes ownership and sells only the right to use the NFT to a third party. It is a method of continuing to maintain ownership of and transferring only the right to use (right to inquire) to a third party, like the right to license a patent.
  • this method can be a profit model for individuals who do not want to completely sell their genomic data, but are selling only the right to use, which is the concept of license.
  • the ownership transaction (sale) of the NFT refers to an online transaction method in which the ownership of the NFT itself is sold and transferred to a third party, and an individual owns his/her NFT (Bio-Arts image + genome data (+ gene prediction report)).
  • this method can be a profit model for individuals who do not mind passing ownership by completely selling their genome data to a third party.
  • NFT consumers are expected to be research institutes, hospitals, companies, etc. that require genomic data, and a gene prediction report for providing not only primitive genomic data but also standardized individual genetic characteristic data
  • a gene prediction report for providing not only primitive genomic data but also standardized individual genetic characteristic data
  • the NFT payment processing unit 320 processes the NFT payment using cryptocurrency according to the transaction application contents (NFT usage right transaction, ownership transaction) of the NFT transaction application unit 310, and upon completion of the payment, the NFT transaction application unit 310 It is possible to provide the NFT buyer with an encryption key and a decryption key to confirm the requested NFT image and the genome data matched with the NFT image.
  • Solana coin can be applied to cryptocurrency or virtual currency used for NFT conversion and trading, but it is not limited to these specific coins.
  • the advantages of Solana coin are its high transaction speed and low transaction cost, and it can provide a more secure smart contract model.
  • Zerocoin is the calculation of the value of 1 coin as a unit of human lifespan. Regardless of which unit is used, such as hour, second, minute, or day, everything belongs to the concept of zerocoin. This is a concept coined by translating the core of the monetary concept into all goods, services, and capital that can increase or decrease human lifespan.
  • FIG. 15 is a flowchart showing the entire process of an integrated management method for generating, distributing, and trading NFTs based on genomic data according to another embodiment of the present invention
  • FIG. 16 is a bio-arts image generation according to another embodiment of the present invention.
  • a flow chart showing steps Figure 17 is a flow chart showing the NFT generation management step according to another embodiment of the present invention
  • Figure 18 is a flow chart showing the online NFT transaction step according to an embodiment of the present invention.
  • an integrated management method (S1000) for generating, distributing, and trading NFTs based on genome data includes a bio-arts image generation step (S100), an NFT generation management step (S200) And it may include at least one of the online NFT transaction step (S300).
  • Bio-Arts image can be created by converting the genotype information included in the genome data of the Geno-Eye algorithm into color information.
  • the Geno-Eye algorithm means a processor for generating a unique mark that is the signature of the algorithm and contains actual genome sequence information and cannot be imitated by anyone, and creates a new genre of artistic image and corresponding It can play a role in breathing life into an image.
  • the genome data may be data of 100 MB or less parsed by the Geno-Eye algorithm, but the data capacity of the genome data is not limited.
  • the bio-arts image generation step (S100) includes an RGB hexacode conversion step (S110), a unique image generation step (S120), a gene group designation step (S130), and a gene group image conversion step.
  • S140 and artificial intelligence image combination step (S150) may include at least one.
  • the RGB hexacode conversion step (S110) converts at least one genotype information of genome sequence information and mutation information of genome data into RGB hexacode that can be expressed in RGB color. It can (1, 2).
  • this RGB hex code conversion step (S110) one hex code and a combination of a plurality of genotype information correspond to each other to convert the corresponding genome data into RGB hex code based on predefined RGB hex code conversion information.
  • Each genotype information combination of genome data is converted into a corresponding RGB hexadecimal code, and the converted RGB hexadecimal code can be designed to be expressed in a color composed of corresponding RGB.
  • the result of converting the genome data into RGB hexa code may vary depending on the characteristics and size of the input genome data.
  • a unique image based on RGB hexadecimal code may be generated by converting the RGB hexadecimal code converted through the RGB hexadecimal code conversion step (S110) into a two-dimensional figure composed of RGB colors.
  • the RGB hexacode based on genome data is expressed as a band or block (role of skeleton) composed of RGB colors, and the process of attaching flesh to the skeleton by arranging colors according to the designed band or block can proceed (3).
  • the unique image when there is no gene prediction report including at least one gene characteristic test result for genome data, the unique image may be provided as a bio-arts image.
  • the gene prediction report can be omitted if the genome data provider has not selected or does not want to, so if the gene prediction report does not exist, a unique image can be applied as a bio-arts image.
  • the gene group specifying step (S130) if there is a gene prediction report at the request of the genome data provider who provided the genome data, the gene characteristics of the corresponding gene prediction report are analyzed, and the gene characteristics provided as a result of the analysis are analyzed in advance. It can be specified as any one group among a plurality of categorized gene groups. For example, as shown in FIG. 7, if a genome data provider wants to be provided with a gene prediction report, the gene characteristics of the provider are analyzed (1), and based on this, disease information, physical characteristics information, and disease risk are analyzed. The analysis result of information, etc. can be compared with predefined category information to be identified as a gene group of a specific category (2).
  • an image source is set in advance for each gene group, so that the gene group specified through the gene group specifying step (S130) can be converted into a preset image source. For example, as shown in FIG. 7, when it is specified as gene group 2, find a preset image source for gene group 2, match the image source with gene group 2, and provide an image source for gene group 2. By doing so, the individual's genetic prediction report can finally be converted into an image source.
  • a bio-arts image may be generated by combining a unique image and an image source through a predefined artificial intelligence random algorithm.
  • the unique image is an image based on RGB hexadecimal code generated using genome data
  • the image source is an image generated based on a gene prediction report.
  • the artificial intelligence random algorithm can generate a unique Bio-Arts Image by receiving these two images and performing random color combination operations.
  • the bio-arts image generated through the bio-arts image creation step (S100) may be converted into an NFT image and stored and managed.
  • the NFT generation management step (S200) may include at least one of an NFT conversion step (S210), an NFT storage management step (S220), and an NFT providing step (S230), as shown in FIG.
  • a Bio-Arts image may be converted into an NFT image, and an encryption key and a decryption key may be generated upon conversion of the NFT image. Since NFT image conversion can be performed using a known NFT image conversion algorithm, a detailed description thereof will be omitted. However, when converting NFT images, genome data or information on genome data and gene prediction reports may also be encrypted, and at this time, an encryption key and a decryption key may also be generated.
  • the NFT image, encryption key, and decryption key generated through the NFT conversion step (S210) can be stored on a blockchain network, and the corresponding data can be used through blockchain identity authentication .
  • the NFT image stored on the blockchain network, the encryption key, and the decryption key may be delivered to the NFT buyer.
  • online transaction for NFT images may be brokered.
  • the online NFT transaction step (S300) may include at least one of an NFT transaction request step (S310) and an NFT payment processing step (S320), as shown in FIG.
  • NFT transaction application step (S310) basic information (gender, age, occupation, etc.) of the provider of the NFT image and corresponding genome data may be provided, and at least one of the NFT image license transaction and ownership transaction may be applied for. .
  • the transaction (sale) of the NFT license means an online transaction method in which the genome data provider takes ownership and sells only the right to use the NFT to a third party. It is a method of continuing to maintain ownership of and transferring only the right to use (right to inquire) to a third party, like the right to license a patent.
  • this method can be a profit model for individuals who do not want to completely sell their genomic data, but are selling only the right to use, which is the concept of license.
  • the ownership transaction (sale) of the NFT refers to an online transaction method in which the ownership of the NFT itself is sold and transferred to a third party, and an individual owns his/her NFT (Bio-Arts image + genome data (+ gene prediction report)).
  • this method can be a profit model for individuals who do not mind passing ownership by completely selling their genome data to a third party.
  • NFT consumers are expected to be research institutes, hospitals, companies, etc. that require genomic data, and a gene prediction report for providing not only primitive genomic data but also standardized individual genetic characteristic data
  • a gene prediction report for providing not only primitive genomic data but also standardized individual genetic characteristic data
  • the NFT payment processing step (S320) processes the NFT payment using cryptocurrency according to the transaction application details (NFT license transaction, ownership transaction) of the NFT transaction request step (S310), and upon completion of the payment, the NFT transaction application step (S310 ) to provide the NFT buyer with an encryption key and a decryption key to confirm the NFT image requested through the NFT image and the genome data matched with the corresponding NFT image.
  • Solana coin can be applied to cryptocurrency or virtual currency used for NFT conversion and trading, but it is not limited to these specific coins.
  • the advantages of Solana coin are its high transaction speed and low transaction cost, and it can provide a more secure smart contract model.
  • Zerocoin is the calculation of the value of 1 coin as a unit of human lifespan. Regardless of which unit is used, such as hour, second, minute, or day, everything belongs to the concept of zerocoin. This is a concept coined by translating the core of the monetary concept into all goods, services, and capital that can increase or decrease human lifespan.
  • NFT through bio-arts of DNA-based genomic information can be bio-artsed by encoding the epigenome, which is a genome that changes according to the environment or in the same general form.
  • the genome or transcript information which is one step further from the gene, can also become bio-arts specialized for each individual or individual's unique state (time or environmental information).
  • sequences that have actual biological functions can also be NFTized according to the same principle.
  • sequences that have actual biological functions can also be NFTized according to the same principle.
  • individual clinical information or individual animal clinical information is mixed with genome or genetic information and coded, it is further fused to become unique digital information, which can be converted into bio-arts and NFT.

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Abstract

La présente invention concerne un système de gestion intégré pour générer, faire circuler et échanger des JNF en fonction de données génomiques et un procédé associé. La présente invention permet de résoudre le problème que constitue la fourniture d'une plate-forme sur laquelle des données génomiques personnelles peuvent être segmentées en un JNF, mémorisées et gérées de manière stable sur la chaîne de blocs, mises en circulation et échangées en ligne. Par exemple, l'invention concerne un système de gestion intégré pour générer, faire circuler et échanger un JNF en fonction de données génomiques, le système de gestion intégré comprenant : une unité de génération d'image de bio-art pour générer une image de bio-art en convertissant des informations de génotype incluses dans les données génomiques en informations de couleur ; une unité de génération et de gestion de JNF pour convertir l'image de bio-art en une image de JNF et stocker et gérer l'image de JNF ; et une unité de marché de JNF en ligne pour la médiation de l'échange en ligne de l'image de JNF.
PCT/KR2022/018152 2021-11-30 2022-11-17 Système de gestion intégré pour générer, faire circuler et échanger des jnf en fonction de données génomiques et procédé associé WO2023101272A1 (fr)

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KR102438223B1 (ko) * 2021-11-30 2022-09-01 주식회사 클리노믹스 게놈데이터 기반의 nft 생성, 유통 및 거래를 위한 통합 관리 시스템 및 그 방법
KR102508547B1 (ko) * 2022-09-02 2023-03-09 주식회사 메디클라우드 Nft화된 유전자 정보 기반 사용자 인증 방법, 장치 및 시스템
KR102535319B1 (ko) * 2022-09-02 2023-05-26 주식회사 메디클라우드 블록체인 기반 유전자 정보 거래 서비스 제공 방법, 장치 및 시스템

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102438223B1 (ko) * 2021-11-30 2022-09-01 주식회사 클리노믹스 게놈데이터 기반의 nft 생성, 유통 및 거래를 위한 통합 관리 시스템 및 그 방법

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20090082553A (ko) 2008-01-28 2009-07-31 주식회사 지앤시바이오 디엔에이 염기서열을 이용한 이미지 생성 방법 및 시스템
KR102040509B1 (ko) 2019-05-10 2019-11-06 주식회사 나노컴퍼니 유전정보를 이용한 캐릭터 이미지 생성 장치, 방법 및 그 방법의 프로그램이 저장된 기록매체

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102438223B1 (ko) * 2021-11-30 2022-09-01 주식회사 클리노믹스 게놈데이터 기반의 nft 생성, 유통 및 거래를 위한 통합 관리 시스템 및 그 방법

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
DOO-RI LEE: "MyGenomeBox, My Genome Data "Tangible Assets with NFT"", TODAY MONE NEWS, 24 November 2021 (2021-11-24), XP093069000, Retrieved from the Internet <URL:https://news.mt.co.kr/mtview.php?no=2021112415181311305> [retrieved on 20230731] *
JI-EUN LEE: "NFT auction containing 'human DNA' on the open sea digital market", BLOCKCHAIN TODAY, 16 April 2021 (2021-04-16), XP093069008, Retrieved from the Internet <URL:https://www.blockchaintoday.co.kr/news/articleView.html?idxno=16193]> [retrieved on 20230731] *
KOEPSELL DAVID: "DNA, NFTs, and ART", DATASERIES, 30 April 2021 (2021-04-30), XP093069003, Retrieved from the Internet <URL:https://medium.com/dataseries/dna-nfts-and-art-50610561d844> [retrieved on 20230731] *
SIMON JOHNSON: "Creating Generative Art NFTs from Genomic Data", TOWARDS DATA SCIENCE, 9 October 2021 (2021-10-09), XP093068996, Retrieved from the Internet <URL:https://towardsdatascience.com/creating-generative-art-nfts-from-genomic-data-16a48ae4df99> [retrieved on 20230731] *
SIRAJ RAVAL: "Mint a Genome NFT (AlphaCare: Episode 4)", YOUTUBE, 25 October 2021 (2021-10-25), XP093068993, Retrieved from the Internet <URL:https://www.youtube.com/watch?v=XOCuQAKhsMw> [retrieved on 20230731] *

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