Abstract
New genomic and proteomic technologies provide measurements of thousands of features for each case. This provides a context for enhanced discovery and false discovery. Most statistical and machine learning procedures were not developed for the p>>n setting and the literature of DNA microarray studies contains many examples of mis-use of analytic and computatinal methods such a cross-validation. This paper highlights some of key aspects of p>>n problems for identifying informative features and developing accurate classifiers.