About
The human DNA blockchain marketplace is made up of about a dozen companies that do not yet have enough consumer participants (each chain has about 1k users) to interest significant and ongoing purchases of data. An avalancheavax subnet could enable these multiple blockchains to aggregate their user's data and these could be traded to researchers and pharmacists as NFTs given the inclusion of 1024 bytes of payload data along with transfer of such tokens. This project will show the feasibility of such a transactional environment for trade in small portions of DNA sequence space by sorting DNA sequences into sequence groups relatively centered around known single nucleotide polymorphisms so as to establish valuable classes of mutation contexts for medically justified research and development.
Problem
In order to improve the study and the research on health care industry, the researchers need to gather people's DNA sequences as much as possible to help them to find better treatments and cures for diseases. The researchers struggle to get the newest and updated human DNA on time. Patients are preferred to choose personalized medicine, so stored DNA tokens are their simple and convenient way to get their prescription.
Goal
This project is set up to show that small amounts of the sequences can be sent and received easily and cheaply. It secures and protects the DNA providers' sequences. It helps patients to get personalized medicines and also anonymously provides the data to medical researchers.
Users
- Medical experts/specialists who need small amounts of the DNA to do research and data collections.
- Biology tech companies who need DNA trade info and DNA blockchain to improve health care system and industry.
- Patients and healthy conditioned person who are interested in DNA blockchain to use the platform to share their DNA to get personalized drugs and contribute their DNA data to the medical industry.
- Biology learner who are interests to learn and trade.
Solution
This will be a simple DNA trading platform for patients and medical researchers.
Built With
- adobe-illustrator
- adobexd
- avalanche.js
- node.js
- python
- r
- vue
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