235 Copyright © 2017, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 10 DOI: 10.4018/978-1-5225-0914-1.ch010 ABSTRACT This chapter describes the use of fuzzy set theory and intuitionistic fuzzy set theory in DNA sequence comparison. It also shows an indirect application of fuzzy set theory in comparing protein sequences. In fact, protein sequences consist of 20 amino acids. The chapter shows how such amino acids can be classifed in six diferent groups. These groups are obtained purely from theoretical considerations. These are entirely diferent from the known groups of amino acids based on biological considerations. Also it is known how these classifed groups of amino acids help in protein sequence comparison. The results of comparison difer as the groups difer in number and their compositions. Naturally it is expected that newer results of comparison will come out from such newer classifed groups of amino acids obtained theoretically. Thus fuzzy set theory is also useful in protein sequence comparison. INTRODUCTION This chapter highlights the importance of fuzzy set theory and intuitionistic fuzzy set theory in problems of Bioinformatics. Initially the standard Voss numerical representation of Nucleotides is interpreted by a two valued logic. While generalizing it to a polynucleotide or a whole genome, it is shown how the notion of fuzzy logic comes into play and helps in obtaining their representations finally on a 12 dimensional unit hypercube. Naturally the set of poly-nucleotides or of whole genomes may be thought of as forming a metric space under suitable metric. The metric defined this way helps in comparison of DNA sequences. Sometimes the comparison is found to be unsatisfactory. This is compensated by us- ing intuitionistic fuzzy set theory in place of fuzzy set theory and adopting same procedure as in fuzzy Use of Fuzzy Set Theory in DNA Sequence Comparison and Amino Acid Classifcation Subhram Das Narula Institute of Technology, India Soumen Ghosh Narula Institute of Technology, India Jayanta Pal Narula Institute of Technology, India Dilip K. Bhattacharya University of Calcutta, India