Microarray gene expression experiments

Xjk= expression ratio of / gene in experiment (one entry of the gene expression matrix (nxm) from cDNA microarray experiments) yik = expression ratio of cluster in k experiment (cluster locations calculated/predicted by GA)... 

The minimum information about a published microarray based gene expression experiment includes the following six parts ... 

Microarray experiments generate large and complex data sets that constitute e.g. lists of spot intensities and intensity ratios. Basically, the data obtained from microarray experiments provide information on the relative expression of genes corresponding to the mRNA sample of interest. Computational and statistical tools are required to analyze the large amount of data to address biological questions. To this end, a variety of analytical platforms are available, either free on the Web or via purchase of a commercially available product. 

Abbreviation Bp, nucleotide base pairs cDNA, complementary DNA ChIP, chromatin Immunoprecipi-tation Cy5, cyanine 5-dCTP Cy3, cyanine 3-dCTP ESTs, expressed sequence tags FDR, false discovery rate MIAME, minimum information about a microarray experiment mRNA, RNA, messenger NIA, National Institutes of Aging RFUs, relative fluorescence units RT-PCR, reverse transcriptase polymerase chain reaction SAGE, serial analysis of gene expression SAM, significance analysis of microarrays... 

In this review we focus on the use of DNA microarrays for the purpose of differential gene expression analysis. Discussions are intended to provide an overview of DNA microarray technology focusing on themes currently believed important to ensuring a successful DNA microarray experiment. Specifically, we address practical issues surrounding the use of DNA microarray technology with emphasis placed on its utility in the investigation of experimental stroke. 

The growing commercial availability and relative affordability of cDNA microarrays combined with well-defined protocols for hybridization has made functional genomics a reality for many laboratories. However microarray experiments produce massive quantities of gene expression and functional genomics data, the analysis of which is complicated and involves many steps, each requiring careful consideration. 

Dudoit S, Yang YH, Callow MJ, Speed TP. 2002. Statistical methods for identifying differentially expressed genes in replicate cDNA microarray experiments. Statistica Sinica 12 111. 

Pan W, Lin J, Le G. 2002. How many replicates of arrays are required to detect gene expression changes in microarray experiments A mixture model approach. Genome Biology 3(5) research0022.1. 

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