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High throughput genomic techniques produce datasets involving thousands of gene expression profiles. In order to infer biologically meaningful regulatory interactions, a dimensionality reduction must take place to identify genes or groups of genes that are important to the biological system being analyzed. Here we provide a systematic approach to remove dispersible genes from consideration based on...
Complex clinical phenotypes arise from the concerted interactions among the myriad components of a biological system. Therefore, comprehensive models can only be developed through the integrated study of multiple types of experimental data gathered from the system in question. The Random Foreststrade(RF) method is adept at identifying relevant features having only slight main effects in high-dimensional...
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