A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes.

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis.

Detection of Novel Genomic Markers for Predicting Prognosis in Hepatocellular Carcinoma Patients by Integrative Analysis of Copy Number Aberrations and Gene Expression Profiles: Results from a Long-Term Follow-Up.

The aim of this study was to explore novel genomic biomarkers predicting hepatocellular carcinoma (HCC) prognosis by integrative analysis of DNA copy number aberrations (CNAs) and gene expression profiles. Array comparative genomic hybridization and expression array were performed on 45 and 31 HCC samples, respectively. To identify functionally important genes, concordant results of DNA copy number and gene expression were retrieved by integrative analysis.

Patterns of gene expression associated with Pten deficiency in the developing inner ear.

In inner ear development, phosphatase and tensin homolog (PTEN) is necessary for neuronal maintenance, such as neuronal survival and accurate nerve innervations of hair cells. We previously reported that Pten conditional knockout (cKO) mice exhibited disorganized fasciculus with neuronal apoptosis in spiral ganglion neurons (SGNs). To better understand the genes and signaling networks related to auditory neuron maintenance, we compared the profiles of differentially expressed genes (DEGs) using microarray analysis of the inner ear in E14.