Cross-platform comparison of microarray-based multiple-class prediction.

ABSTRACT: High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether p

SUBMITTER: Fan X 

PROVIDER: S-EPMC3019174 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature