Visualization, Screening and Classification of Cell Cycle-Regulated Genes in Yeast by Multidimensional,Scaling,Nonlinear Dimension Reduction and Wavelet Transform

Abstract

We propose a new and integrated approach for visualization, screening, and prediction of gene functions using microarray data, based on multidimensional scaling (MDS), nonlinear dimension reduction and wavelet transform. This approached is applied to analyze the cell cycle of yeast in Spellman et al. (1998). The results show that this new approach indeed provides a visualization tool, which displays the functional relationships between genes, like the periodical pattern of a cell cycle. This representation can be used to verify the functions of genes known by experimental methods in literature. Based on this, screening and prediction of the functions of all genes can be implemented. The performances of different methods in screening and prediction are evaluated by the Jackknife approach and compared in this study. Hence, this integrated approach suggests a new perspective to classify and discover the functions of genes by their expression profiles in microarray. The findings for yeast cell cycle are also reported and discussed.