Sentence examples for microarray dataset with from inspiring English sources
A large merged breast cancer DNA microarray dataset with 689 pretreatment samples [28], [29], [30] and an ovarian cancer dataset with 274 treated patients [31] were used for the analysis.
The gene sets were paired to a microarray dataset with the same tissue type.
As a result, we could get a microarray dataset with 6688 distinct genes and 237 samples.
To compare minipig tissue expression profiles to their human counterparts, we used a high quality human microarray dataset with 13 overlapping tissues and 16,032 shared genes [ 30].
We then constructed a functional linkage network by integrating the microarray dataset with the pathway database of Kyoto Encyclopedia of Genes and Genomes (KEGG).
Inspired by the idea of COREG, for a microarray dataset with a large missing rate, we treat the complete and incomplete genes as labeled and unlabeled examples correspondingly.
The proposed framework of system has been tested on two well-known tumor microarray datasets with encouraging results and shown great potential for the developments of generic platform for tumor clinical diagnosis based on microarray data.
Simulation studies indicated that Messina reliably detected inconsistent differential expression in complex microarray datasets with few samples per group.
In order to test Messina's detection performance, we produced a series of simulated microarray datasets with known differential expression using data from a previously-published study [8].
As a proof of concept, we have used this method to analyze three public microarray datasets with a direct comparison with the GSEA method, one of the most popular pathway-level analysis methods in the field.
Here we proposed an inter-study analysis combining results from the five published microarray datasets with our dataset of genes differentially expressed during the murine estrous cycle [13], to address the hypothesis that genes involved in normal ovarian surface epithelium functions, such as ovulation, are aberrantly expressed in ovarian cancer.
