Gene Structure Analysis System

In today’s world, to be able to find out the statistical significance between nucleotides or protein sequence databases is an important part of the discovery of the details of genome and correlation patterns. A very important aspect of the development of society as a whole depends on the discovery of ‘what was’ and ‘what could be’. And it cannot be done without taking a deeper look into the genetics of mankind. The development in the field of genetics has not only helped the world of medicine in excel in various aspects but also helped mankind to find out the solution to many unsolvable health issues. Hence, ‘what could be’ can be derived from ‘what was’ and to do that, we need to take a closer look at the data that we already have, i.e. our genes. This system will receive necessary data from the given databases and will allow users to choose from a list of suitable algorithms and hence provide all the subsequent results that can be figured out from the processed data. The interface will be able to implement and compare the results of two given sets of algorithms and display the most likely output. To implement the algorithms, a certain type of Machine Learning techniques such as K-mean clustering, Neural Network Approach for Pattern Recognition, and Agglomerative clustering is also used. The resultant data can be instrumental in shaping the future. Based on the genetic algorithms and the comparison between their results, we can make various deductions which can help in the invention of new drugs, or simply understanding our own body.