Implementation of Longest Common Subsequence Algorithm Using Thread Parallelization in Java

This sequence alignment stands as a pivotal method in the realm of bioinformatics, meticulously employed to ascertain the degree of similarity between diverse sequences such as DNA, RNA, and amino acids. Among the myriad techniques utilized in tackling sequence alignment challenges, the Longest Common Subsequence (LCS) takes center stage. This paper delves into the realm of enhancing LCS efficiency through the implementation of thread parallelization. Drawing inspiration from the seminal work of Wagner and Fischer in 1974, both sequential and parallel techniques exhibit remarkable consistency in identifying the maximum length of LCS. However, this research goes a step further by introducing thread parallelization, which leverages multithreading, resource synchronization, and task decomposition within the domain of parallel programming. The meticulous integration of these advanced techniques results in a notable enhancement in terms of running time compared to the conventional iterative sequential approach. The experimentation and evaluation of both sequential and parallel approaches were conducted using Netbeans, a robust Integrated Development Environment (IDE) tailored for the Java Programming Language. The findings underscore the superior performance of the thread parallelization strategy, establishing its prowess in optimizing the execution time of LCS problem resolution.