Chronological Pattern Exploration Algorithm for Gene Expression Data Clustering and Classification

Abstract

In medical data, prediction of a disease in diagnosis and drug determination depends upon the type of the disease. Previous disease classification approaches are clinically based and the ability of the diagnostic process is restricted. In recent days DNA/RNA microarray techniques can monitor more number of gene expression data. Using this ability the medical research people started exploring the various ways of classifying the disease from genetic data. All the methods are promising on producing results. Even though there are some issues which should be handled to improve the accuracy of classification. Classification of the disease depends on data clustering so that, this paper concentrates on clustering the data efficiently and mine for the more accurate pattern using Chronological Pattern Exploration (CPE) as an effective pattern matching approach. This CPE algorithm investigates the data by means of attributes, metadata and the meaning of the data to the search pattern. The simulation of this approach is carried out in MATLAB software to authenticate the efficiency.