Fuzzy set-based microarray data analysis techniques for interesting block identification

Microarrays are one of biotechnology products which enable to measure the expression level of thousands of genes simultaneously. It is sometimes crucial to identify some interesting blocks from microarray data for further investigation. Due to the massive volume of data, it is desirable to get assistance of software tools to handle this task. This paper introduces three fuzzy set-based microarray data analysis techniques used to find local cluster, to locate contrasting group, and to filter group with specific pattern.