Design And Implementation Of Gene Microarray Data Classification System

Genes determine all manifestation of life from birth to death throughout life.Through genetic testing and data analysis can help people know the direction of human diseases and potential pitfalls,and guide medicine to a more accurate direction of treatment.Gene expression data is obtained by microarray technology,DNA microarray technology,has also been a gene chip technology.Through gene microarray technology,people can get a lot of gene expression data.The analysis and research of cancer gene data with biological information will help to predict and diagnose the disease.However,how to have the data of high dimension,small samples,correlation,redundancy and noise characteristics of interference characteristics of the gene microarray data for rapid,efficient and accurate extraction and classification,has become one of the important topics in the study of gene microarray data.In this paper,based on reading a lot of domestic and foreign literature,a number of experiments on the basis of cancer gene microarray data as the research object,developed a gene microarray data classification system.This paper is composed of feature selection,feature extraction and classification of gene microarray data.In the part of feature selection and feature extraction,the wavelet transform is used to reduce the dimension quickly and reduce the influence of redundant feature data on sample classification.In view of the complexity of microarray experiments and the influence of environmental factors,and the differences of data acquisition objects,this makes the same classifier show different learning effects on different data sets.Text will be improved by Borda fusion algorithm,the feature selection method to obtain the characteristics of the sort sequence,fused into an optimal feature sequencing results.At the same time,the particle swarm optimization(PSO)algorithm is used to filter the wavelet coefficients to obtain the optimal feature subset.In order to verify the algorithm can effectively achieve the classification of genetic data,and its system has a certain feasibility and practicality.In this paper,we will carry out experiments on three data sets,namely acute leukemia data sets,prostate data sets,lung cancer data sets.The experimental results show that this method can get better results of microarray data classification.Furthermore,the improved algorithm is applied to the classification system,which not only validates the validity of this algorithm,but also verifies the rationality and usability of the gene microarray data classification system.