CORE--STATISTICAL ANALYSIS OF TOXICS MEASUREMENT

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The primary role of the statistics core will be to provide consultation on experimental design and assistance with data interpretation for the research projects and other cores. We also will provide database support to projects with particular attention to support of the Analytical Core A and the DNA microarray Core C. A new emphasis will be in the area of bioinformatic support. We will develop methods for the storage and interpretation of DNA microarray data and assist with pattern recognition systems with pattern recognition systems for proteomic and metanomic approaches. In addition we will develop new statistical methods for the emerging field of microarrays. We will continue our work on developing statistical methods for immunoarrays and other information systems with high density. Techniques such as Bayes estimation, non-linear optimal design, maximus pseudo likelihood, and M estimation will be employed. We propose the development and refinement of statistical methods and algorithms for the analysis of hazardous chemicals and for the creation of new and improved measurement techniques. This will be particularly important with the analysis of data from accelerator mass spectroscopy. We will deal with problems including non-linear calibration, non-constant variance, possible outliers, values near or below detection limits and high- dimensional and large data sets. These goals will be accomplished in five specific aims including: collaboration with other investigators with other investigators on statistical questions, develop new statistical methods for problems commonly encountered in hazardous chemical research, apply state-of-the-art techniques in numerical analysis and numerical optimization to develop efficient, fast, and reliable computer algorithms to solve problems in implementing statistical methods, develop software incorporating the above developments in statistical methodology and numerical methods for laboratory use, assist with bioinformatic problems induced by the complexly structured data files, and conduct outreach activities to transfer new statistical technology to the environmental and regulatory community.