Systems biology researchers often rely on the use of one or more pathway resources for
analysis of gene expression data or experimental results. Unfortunately, there is no single …

To microarray expression data analysis, it is well accepted that biological knowledge-guided
clustering techniques show more advantages than pure mathematical techniques. In this …

Background The application of pathway and gene-set based analyses to high-throughput
data is increasingly common and represents an effort to understand underlying biology …

Background The gene shaving algorithm and many other clustering algorithms identify gene
clusters showing high variation across samples. However, gene expression in many …

Motivation: By capturing various biochemical interactions, biological pathways provide
insight into underlying biological processes. Given high-dimensional microarray or RNA …

Cluster analysis is usually the first step adopted to unveil information from gene expression
data. One of its common applications is the clustering of cancer samples, associated with the …

Background As numerous diseases involve errors in signal transduction, modern
therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of …

It is commonly accepted that genes with similar expression profiles are functionally related.
However, there are many ways one can measure the similarity of expression profiles, and it …

Analyzing gene expression patterns is a mainstay to gain functional insights of biological
systems. A plethora of tools exist to identify significant enrichment of pathways for a set of …

We developed PathAct, a novel method for pathway analysis to investigate the biological
and clinical implications of the gene expression profiles. The advantage of PathAct in …