Adapting normalized google similarity in protein sequence comparison

Abstract

Biological sequence comparison faced various challenges. Although dynamic programming based solution claimed to be the optimal solution for the comparison process, the computation limitation and some fundamental challenges still make it inefficient for mass sequence comparison. Statistical method explores the statistics of sequences by the frequency of the words in the sequence; it provides a comparison solution without loss of statistical information, and also caters some of the fundamental problem in sequence comparison. Normalized Google Distance is a way of finding semantic similarity in web pages, with significant related characteristics; in this research, we propose an algorithm that will integrate Normalized Google Similarity into protein sequence comparison.