Analysis of Polynucleotide Sequences for Fuzzy Genomes: A Juxtaposition of Two Fuzzy Approaches

The Human Genome Project is the resplendence of the bioinformatics field, especially in health and medicine. It involves research regarding complete nucleotide sequences of the deoxyribonucleic acid (DNA) in human’s chromosome. The primary structure of DNA and ribonucleic acid (RNA) consist of nucleotide construction which became polynucleotide when combined. In reality, genetic research field requires huge biological data, and most of the data are vague with various characteristics. Most of them are incomplete and complex from evolutional, functional, adaptability and other traits. The theory of fuzzy sets and fuzzy logic offers modelling methods in uncertainties and various computational techniques for decision making. This research aims to find similarity, difference, equality and identity between polynucleotide sequences using the concept of fuzzy metric space and fuzzy set theory. The Sadegh-Zadeh fuzzy polynucleotide space (RSZ) is being compared with the Torres and Nieto fuzzy polynucleotide space (RTN) in search of the best approach to analyse polynucleotide sequences. Research methods involve data collection of complete genome sequences for homologous species pairs, construction of the RSZ and RTN models, and data analysis. Outputs from RSZ and RTN are then compared with outputs from the Basic Local Alignment Search Tool (BLAST) for validation purposes from the bioinformatics field. Results show that outputs from both approaches are against each other, and RTN executes outputs that are nearest to the outputs from BLAST. Thus, RTN is the best fuzzy approach to compare complete genome sequences for species pairs.