Currently we have lots of computational data related to cancer and solving the big problem. However, instead of cancer researchers and biologist solving it, I think the problem lies in the hand of big data developers. This is why I started working on an algorithmic solution utilizing data visualization software such as RapidMiner Studio and/or hadoop extensions to build something unlike anything in the market already.
This is what I done:
Knowing how fast it takes Microsoft to calculate the human genome, I wanted to do something further with some of that data. Many open bio portals have lots of genomic cancer case studies in the public domain, and this is where the inspiration came from. I want to be able to build a cloud repository and create an API that can compress and mine through hundreds of thousands of cancer case studies and visualize the most important ones at once, draw conclusions using MD5 data, and perform experimental analysis.
The solution impact is coming up with better ways in order to look at genomic case studies and maybe in the future potentially solve fatal diseases.
https://www.academia.edu/37722328/Utilizing_RapidMiner_for_Cancer_Genomics_and_Mutation_View_Counts
Data mining and big data has capabilities of running faster obviously on a 5G network in comparison to a 4G one. However, people being able to start building data centers that can recursively and regressionally analyze diseases is the future. This is why you have big genomics companies like Tempus out there. I feel like this is the future of medicine. Also if we win, we plan on running this ontop of a decentralized OS we developed in order to better decentralize the genomic data mining process.
