Improving the prediction accuracy in classification using the combined data sets by ranks of gene expressions

Background: The information from different data sets experimented under different conditions may be inconsistent even though they are performed with the same research objectives. More than that, even when the data sets were generated from the same platform, the data agreement may be affected by the technical variation among the laboratories. In this case, it is necessary to use the combined data set after adjusting the differences between such data sets, for detecting the more reliable information. Results: The proposed method combines data sets posterior to the discretization of data sets based on the ranks of the gene expression ratios, and the statistical method is applied to the combined data set for predictive gene selection. The efficiency of the proposed method was evaluated using five colon cancer related data sets, which were experimented using cDNA microarrays with different RNA sources, and one experiment utilized oligonucleotide arrays. NCI60 cell lines data sets were used...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Ki-Yeol Kim, Dong Hyuk Ki, Hei-Cheul Jeung, Hyun Cheol Chung, Sun Young Rha
• Keywords: BMCBI 2008, Data Sets, Gene Expressions, Separated Data Sets