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GSE21031
Mus musculus
12 Downloadable Samples
Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
External stimulations of cells by hormones, growth factors or cytokines activate signal transduction pathways that subsequently induce a rearrangement of cellular gene expression. The representation and analysis of changes in the gene response is complicated, and essentially consists of multiple layered temporal responses. In such situations, matrix factorization techniques may provide efficient tools for the detailed temporal analysis. Related methods applied in bioinformatics intentionally do not take prior knowledge into account. In signal processing, factorization techniques incorporating data properties like second-order spatial and temporal structures have shown a robust performance. However, large-scale biological data rarely imply a natural order that allows the definition of an autocorrelation function. We therefore develop the concept of graph-autocorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways as a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the samples to define an autocorrelation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph decorrelation (GraDe) algorithm. To analyze the alterations in the gene response in IL-6 stimulated primary mouse hepatocytes by GraDe, a time-course microarray experiment was performed. Extracted gene expression profiles show that IL-6 activates genes involved in cell cycle progression and cell division in a time-resolved manner. On the contrary, genes linked to metabolic and apoptotic processes are down-regulated indicating that IL-6 mediated priming rendered hepatocytes more responsive towards cell proliferation and reduces expenses for the energy household.
Publication Title
Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation.
Sample Metadata Fields
Specimen part, Treatment, Time
View Samples- Homo sapiens
- 294 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
A formalin-fixed paraffin-embedded (FFPE)-based prognostic signature to predict metastasis in clinically low risk stage I/II microsatellite stable colorectal cancer.
Sample Metadata Fields
Sex, Age
View Samples- Homo sapiens
- 150 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
This study was conducted in order to identify biomarkers for a prognostic gene expression signature for metastases in early stage CRC.
Publication Title
A formalin-fixed paraffin-embedded (FFPE)-based prognostic signature to predict metastasis in clinically low risk stage I/II microsatellite stable colorectal cancer.
Sample Metadata Fields
Sex, Age
View Samples- Pan troglodytes, Homo sapiens
- 15 Downloadable Samples
- Affymetrix Human Genome U95B Array (hgu95b), Affymetrix Human Genome U95D Array (hgu95d), Affymetrix Human Genome U95 Version 2 Array (hgu95av2), Affymetrix Human Genome U95C Array (hgu95c), Affymetrix Human Genome U95E Array (hgu95e)
Description
Gene expression profiling in brain of three adult humans and three adult chimpanzees
Publication Title
DNA sequence and comparative analysis of chimpanzee chromosome 22.
Sample Metadata Fields
Sex, Age, Specimen part, Disease, Disease stage
View Samples