prostate cancer is the second most common cancer in men. in spite of on-going researches in this filed, the specific causes of prostate cancer are so far unknown. in this study, we used two methods of gene set analysis to improve the biological interpretation of the observed expression patterns in prostate cancer. the gene set analysis is a computational method to discover gene sets whose expre...

Gene expression microarray technologies provide the simultaneous measurements of a large number of genes. Typical analyses of such data focus on the individual genes, but recent work has demonstrated that evaluating changes in expression across predefined sets of genes often increases statistical power and produces more robust results. We introduce a new methodology for identifying gene sets th...

Gene differential expression consists of the study possible association between gene expression, evaluated using different types data as DNA microarray or RNA-Seq technologies, and phenotype. This can be performed marginally for each (differential expression) a set collection (gene analysis). A previous (marginal) per-gene analysis is usually in order to obtain significant genes marginal p-valu...