Motivation: Recent advances in DNA microarray technologies have made it possible to
measure the expression levels of thousands of genes simultaneously under different …

Microarray analysis using clustering algorithms can suffer from lack of inter-method
consistency in assigning related gene-expression profiles to clusters. Obtaining a …

Background A method to evaluate and analyze the massive data generated by series of
microarray experiments is of utmost importance to reveal the hidden patterns of gene …

Probabilistic graphical models combine the graph theory and probability theory to give a
multivariate statistical modeling. They provide a unified description of uncertainty using …

Extracting a comprehensive overview from the huge amount of information arising from
whole-genome analyses is a significant challenge. This review critically surveys the state of …

Whilst China experiences long-term rapid urbanization, urban shrinkage, as a new normal,
has become a common phenomenon in urban development along with growth. In this study …

Cluster analysis of gene-wide expression data from DNA microarray hybridization studies
has proved to be a useful tool for identifying biologically relevant groupings of genes and …

Motivation: The success of each method of cluster analysis depends on how well its
underlying model describes the patterns of expression. Outlier-resistant and distribution …

A limitation of many gene expression analytic approaches is that they do not incorporate
comprehensive background knowledge about the genes into the analysis. We present a …

Background With the increasing amount of data generated in molecular genetics
laboratories, it is often difficult to make sense of results because of the vast number of …