MICROARRAY DATABASE
	In October 2004, the Stanford Microarray Database recorded its 50,000th experiment, marking its place at the forefront of an information processing revolution that has yielded groundbreaking insights into the relationships between genes and illness, as well as fundamental biological discoveries.

Development of Statistical and Computational Tools for Analysis and Interpretation of Large-scale, Systematic Molecular Profiles of Cancer

Over the past decade, the wealth of information generated by the systematic profiling of virtually every kind of human cancer has enabled important advances in the classifications used for cancer diagnosis and treatment planning.

Today program researchers continue to support the timely and effective analysis --and clinical application -- of this ever-growing pool of data through the development of novel computational and statistical strategies.

World-renown for their expertise, these clinicians, experimentalists, statisticians and computational biologists have already pioneered a number of breakthrough applications including:

• The Stanford Microarray Database (SMD), an international resource for the sharing and analysis of DNA microarray data
• Significance Analysis of Microarrays (SAM), which identifies genes with reproducible changes in expression and supplies a false detection rate from permutation of the data
• Predictive Analysis of Microarrays (PAM), which finds and cross-validates genes that classify an unknown sample by proximity to the nearest centroid of gene expression patterns in a training set of samples
• Gene Shaving method, which identifies distinct sets of genes with similar expression patterns
• Novel statistical approaches focused on the problems of cancer diagnosis, classification, prediction of treatment responses and prognosis
• Empirical bayes methods and statistical methods for determining accurate false discovery rates during the analysis of DNA microarray data
• Methods for estimating missing data, supervised harvesting cluster trees during microarray data analysis and transformation
• Software and tools for the analysis and visualization of microarray data, including Caryoscope to visualize array CGH results and GO::TermFinder to identify common biological themes within groups of genes

Program Researchers

Bradley Efron, PhD

Trevor Hastie, PhD

Gavin Sherlock, PhD

Robert Tibshirani, PhD