Clustering microarray gene expression data using type 2 fuzzy logic

Microarray technology helps biologists for monitoring expression of thousands of genes in a single experiment on a small chip. Microarray is also called as DNA chip, gene chip, or biochip is used to analyze gene expression. DNA microarrays are rapidly becoming a fundamental tool in genomic research. Bioinformatics and data mining provide exciting and challenging researches in several application areas especially in computational science. Bioinformatics is the science of managing, mining, and interpreting information from biological sequences and structures. Fuzzy Logic is a multivalued logic that allows intermediate values to be defined between conventional evaluations like true or false, yes or no, high or low, etc. Fuzzy inference rules are used to transform the gene expression levels of a given dataset into fuzzy values. In this paper, Type 2 fuzzy logic approach is used to fuzzify the microarray gene expression data. Then the clustering of genes is done by using clustering algorithms and the cluster results are compared with the proposed Type 2 fuzzy approach.