A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer.

ABSTRACT:

Background

In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of interesting genes or biological pathways. However, in order to analyze the large number of noisy measurements in microarrays, effective and efficient bioinformatics techniques are needed to identify the associations between genes and relevant phenotypes. Moreover, systematic tests are needed to validate the statistical and biological significance of those discoveries.

Results

In this paper, we develop a robust and efficient method for exploratory analysis of microarray data, which produces a number of different orderings (rankings) of both genes and samples (reflecting correlation among those genes

SUBMITTER: Shi F 

PROVIDER: S-EPMC2949898 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature