A Big Data Approach in Mutation Analysis and Prediction
Abstract
Although the technology advancement in the last few years has been exponentially growing, there are still a lot of medical problems that don’'t have an accessible solution. One of these problems is the one that genetics is facing: the absence of a solution for inspecting the previously reported genetic mutations. In order to confirm a mutation, the specialists need to narrow it down based on their experience and, if present, the few documented precedent cases. This paper focuses on presenting a solution for analyzing big amounts of historical genetic data in an efficient, fast and user-friendly way. As a proof of concept, it demonstrates the huge role that Big Data has in genetic mutations aggregation and it can be considered a starting point for similar solutions that aim to continuously innovate genetics. The effectiveness of our proposal is highlighted by comparing it with similar existing solutions.
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