Novel approach to find the optimal alignment using lcmsq algorithm for identifying the various stages of lymphoma

Abstract

Lymphoma is a commonly occurring disease which is seen in coastal areas of Kollam district, Kerala. There are two types of “Lymphoma”, one is Hodgkin and another Non-Hodgkin, Both are caused due to due to mutated Lymphocyte (a type of white blood cells) from gamma radiation. We are considering a small population of people living near coastal area where High Background Radiation (HBR) has been repeatedly shown an increase in the frequency of chromosome aberration in the circulating lymphocytes of exposed person of has leads to unconditional growth of cells. In existing system called LCS (Longest continues subsequence) algorithm is more time consuming and less efficient for finding longest common subsequence and for aligning the sequences. So here we are going to develop an innovative approach for finding the optimal sequence alignment to reduce the time and space complexity and increase the efficiency of sequence alignment in the large data set. Here we are using innovative longest continues matching sequence queue method(LCMSQ) to reduce the execution of time and making it cost effective for optimal sequence alignment. The LCMSQ uses the split method when a match occurs, the sequence split into the left and the right part where we consider the right part of the sequence for finding another match. As a result, we would obtain a maximum possible number of matches when traversed. So here we are aligning the lymphoma sequence using the resultant longest sequence queue data. After aligning the sequence, we would find the various stages of lymphoma based on a number of matches, mismatches, and gaps. Through this work, we are comparing the normal sequence and affected sequence of lymphoma for predicting the different stages of lymphoma.