Exposure to Polychlorobiphenyls (PCBs) is known to cause serious health effects in human but the gene expression profiles leading to development of differnet diseases and disorders are not fully understood. The knowledge of global gene expression will help us to devlop early disease or disorder biomarkers for PCB induced health effects.
Transcriptional profiling and biological pathway analysis of human equivalence PCB exposure in vitro: indicator of disease and disorder development in humans.
Sex, Age, Specimen part, Treatment
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Discovery of drug mode of action and drug repositioning from transcriptional responses.
Specimen part, Cell line, Treatment
View SamplesThe effects of several compounds on the MCF7 human adenocarcinoma mammary cell line were analysed by gene expression profiling.
Discovery of drug mode of action and drug repositioning from transcriptional responses.
Specimen part, Cell line, Treatment
View SamplesThe effects of the CDK inhibitors PHA-848125 and PHA-690509 on the A2780 cell line were analysed by gene expression profiling.
Discovery of drug mode of action and drug repositioning from transcriptional responses.
Specimen part, Cell line, Treatment
View SamplesThe effects of the CDK inhibitor PHA-793887 on the A2780 human adenocarcinoma ovary cell line were analysed by gene expression profiling.
Discovery of drug mode of action and drug repositioning from transcriptional responses.
Specimen part, Cell line, Treatment
View SamplesThe effects of the CDK inhibitor PHA-848125 (referred to as CDK-125) on the MCF7 human adenocarcinoma mammary cell line were analysed by gene expression profiling.
Discovery of drug mode of action and drug repositioning from transcriptional responses.
Specimen part, Cell line, Treatment
View SamplesThe effects of the CDK inhibitor Flavopiridol on the A2780 human adenocarcinoma ovary cell line were analysed by gene expression profiling.
Discovery of drug mode of action and drug repositioning from transcriptional responses.
Specimen part, Cell line, Treatment
View SamplesComparatative gene expression analysis for CD4 T cell subsets isolated from peripheral blood and palatine tonsils
A methodology for global validation of microarray experiments.
Specimen part
View SamplesDNA microarrays are popular tools for measuring gene expression of biological samples. This ever increasing popularity is ensuring that a large number of microarray studies are conducted, many of which with data publicly available for mining by other investigators. Under most circumstances, validation of differential expression of genes is performed on a gene to gene basis. Thus, it is not possible to generalize validation results to the remaining majority of non-validated genes or to evaluate the overall quality of these studies. <br></br> We have devised an approach for the global validation of DNA microarray experiments that will allow researchers to evaluate the general quality of their experiment and to extrapolate validation results of a subset of genes to the remaining non-validated genes. We applied this method to a microarray experiment validated with quantitative real time polymerase chain reaction. The experiment consists of three biological replicate treatments of mouse 3T3-L1 preadipocytes with the steroid hormone dexamethasone for 3 hours. Total RNA was extracted from each of our three treatment and three control samples, and we labeled and hybridized five aliquots of each sample to Affymetrix MGU74Av2 microarrays, for a total of 30 microarrays.<br></br> We illustrate why the popular strategy of selecting only the most differentially expressed genes for validation generally fails as a global validation strategy and propose random-stratified sampling as a better gene selection method. We also illustrate shortcomings of often-used validation indices such as overlap of significant effects and the correlation coefficient and recommend the concordance correlation coefficient (CCC) as an alternative.
A methodology for global validation of microarray experiments.
Cell line, Subject, Compound
View SamplesWe report that knockdown of EJC core proteins, eIF4A3, Y14, Magoh, causes a transcript-wide changes in alternative splicing, as well as some transcriptional changes. These changes are specific to EJC core proteins, and KD of UPF1 protein caused different sets of alterantive splicing changes. These changes are linked to the rate of transcription. Overall design: Examination of 4 different knockdown, as well as GFP knockdown in HeLa cells, 2 replicates each condition.
Transcriptome-wide modulation of splicing by the exon junction complex.
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