Publication

Abstract : pLeukemia is a commonly occurring disease which is mainly seen in Kerala. There are four types of Leukemia, they are, Chronic Myeloid Leukemia (CML), Chronic Lymphocytic Leukemia (CLL), Acute Myeloid Leukemia (AML),Acute Lymphocytic Leukemia (ALL). In this work, we are finding the various stages of Chronic Myeloid Leukemia (CML) using DSDPM algorithm. Chronic Myeloid Leukemia is a cancer of blood or bone-marrowit is the uncontrolled production of blood cells-leukocytes/white blood cells in due to high GAMA radiation. In existing system, when there is huge data, it is inefficient and consumes more time, and multiple comparisons of persons at a time are not possible and finding the stages is difficult. So here we are going to develop an innovative approach for finding the optimal sequence alignment to reduce the time, space complexity and increase the efficiency of sequence alignment in the large data set and find the stages of CML. Here we are using innovative DSDPM algorithm, it is dynamic and recursive optimal distance calculation method to reduce the execution of time and making it cost effective for finding the mutation andoptimal sequence alignment. The DSDPM uses the split distance method. When a match occurs, the sequence split based on distance result and then result will be utilized for next transition. After aligning the sequence, we will find the various stages of CML based on a number of matches, mismatches, and gaps occurred. Through this work, we are comparing the normal sequence and affected sequence of CML for predicting the different stages of CML and find the suitable drug dosagefor CML. © 2018 IEEE./p