In order to compare different risk prediction methods with published gene signatures, we used four large microarray BC datasets collected with Affymetrix microarray platform (22 283 common probes), called VDX (Wang et al., 2005), TBG (Desmedt et al., 2007), TAM (Haibe-Kains et al., 2008; Loi et al., 2007) and UPP (Miller et al., 2005).
Further experiments were conducted on high dimensional microarray gene expression datasets collected online.
Jasmonate treated microarray datasets were collected from NCBI, EMBL, and TAIR.
The advance of high-throughput microarray technique makes it possible to measure the expression profiles of thousands of genes, and genome-wide microarray datasets are collected, providing a way to reveal the complex regulatory mechanism among cells.
The collected microarray datasets were standardized by using quantile normalization.
Three high-throughput DNA methylation microarray datasets (458 samples) were collected in the discovery stage.
In our study, we collected microarray datasets of bladder cancer from GEO http://www.ncbi.nlm.nih.gov/geo/ to analyze the datasets by an integrated strategy including some functions of SAMR[ 15], WGCNA[ 16], Cytoscape[ 17] and other packages.
Through searching and selection, a final list of 3 microarray datasets [ 3, 4] was collected for meta-analysis.
They collected 38 microarray datasets with experimentally determined true DEGS by real-time polymerase chain reaction (RT-PCR).
The Integrative Multi-species Prediction [ 9, 10] webserver has collected over 2,000 microarray datasets from the NCBI Gene Expression Omnibus (GEO), large collection of biochemical experiments from the Database of Protein and Genetic Interactions (BioGRID), tissue-specificity and phenotype characterizations from The Zebrafish Model Organism Database (ZFIN) and other sources for seven organisms.
