Title: Visualization, screening and classification of cell cycle-regulated genes in yeast
by multi-dimensional scaling, nonlinear dimension reduction and wavelet transform

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.