A study of performance of Longest Common Subsequence identification with sequence identity of biosequences

Searching for clue to the result with biosequences is an important area of research for computational scientists in bioinformatics. The sequences are longer and demand more and more computational power in order that the result yields benefits to the society. More often the computational results are used in obtaining quick clue to the expected results of lengthy laboratory process. The identity and similarity between sequences provide the basic clue and guidance as to how to progress with work. This paper analyses SRLCS algorithm with the tools like CLUSTAL-W, and MUSCLE in identifying Longest Common Subsequence (LCS) with reference to identity between the bio sequences.