Sentence examples for cancer expression data from inspiring English sources

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].

We used the WDCM to cluster three cancer gene expression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results.

To test our hypotheses we first integrated a highly curated network of protein interactions (from the Human Protein Reference Database) [ 2] with a high-quality cancer gene expression data set from 286 breast cancer patients [ 23], of which 107 relapsed (Methods).

At first, we reconstructed the human prostate cancer protein-protein interaction network (HPC-PPIN) and the network was then integrated with the prostate cancer gene expression data to identify modules related to different phases in prostate cancer.

We also compared the gene expression profiles in breast cancer tumors of the variant carriers and non-carriers, with further survival analyses on the differentially expressed genes in breast cancer gene expression data sets.

The hub genes of GRNs that were inferred from large-scale cancer gene expression data were observed to provide promising putative novel target genes for cancer such as G-protein coupled receptors and transmembrane proteins [ 10, 12].