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For example, the expression values for the AKT gene, are not only significantly different in both cancer expression data sets, but the value of betweenness centrality and degree are higher than 3.8E-4 and 9.71E-4 9.71E-4specthee averespectives).
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We have applied RIF to both breast cancer and colorectal cancer expression data sets, contrasting them against normal tissue samples.
Met-express is a published method originally applied to cancer expression data.
We used a normalized cancer expression data set previously published [13].
Our analysis of the breast cancer expression data underscores the value of the scale-free structure prior as an instrument to aid in the identification of candidate hub genes with the potential to direct the hypotheses of molecular biologists, and thus drive future experiments.
Normal tissue and human cancer expression data were retrieved from two external data sets.
We thus collected three additional breast cancer expression data sets that had been profiled with Affymetrix arrays [ 24- 26].
The Cancer Genome Atlas (TCGA) breast cancer expression data and clinical annotations were downloaded from the TCGA website [ 18].
PH compiled and analyzed the prostate cancer expression data sets and performed the modeling of transcriptional regulatory networks.
We built normal and cancer networks of miRNA-mediated sponge interactions (MMI-networks) using breast cancer expression data provided by The Cancer Genome Atlas.
At the moment, DRUGSURV covers 44 independent clinical cancer expression data sets (in most cases each data set contains >100 patients annotated with survival information).
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CEO of Professional Science Editing for Scientists @ prosciediting.com