Research on the Gene Sequence Data Mining Model Based on Information Theory and Data Dimension Reduction Algorithm

Abstract

This paper addresses gene sequence data mining model by incorporating information theory and data dimension reduction algorithm. Unlike the previous work focusing more on the issues from the gene's perspective it-self, we combine the information science and data analysis model to achieve better performance. We firstly discuss the state-of-the-art reviews on the data dimension reduction algorithms to serve as the foundation. Later, we address the information theory into the traditional analysis model to synthetize to data analysis process. Then, we revise the basic data mining model with the assistance of the dimension reduction algorithm and information theory. Finally, we simulate the method and compare it with the other approaches and our algorithm out performs compared with the others.