Regular Expression Based Pattern Matching for Gene Expression Data to Identify the Abnormality Gnome

The main idea of this paper is to detect and extract an input pattern from a gene expression dataset. Human behavior and health conditions can be identified and classified through their genomic data in accurate manner. In this paper it is motivated to search and identify the abnormal pattern availability in a gene expression data. To do this a Regular Expression based Pattern Matching (REPM) method is proposed for detecting, identifying and counting number of abnormal pattern occurrences in a given dataset. This approach is experimented in MATLAB software the results verified to check the efficiency of REPM method.