Investigators in this Research Core study and develop methods to analyze the vast amounts of data produced by new technolgies, such as microarrays, used to analye genomes (all the genes in an organism) as well as the proteins and other substances cells produce under various environmental conditions. Overview Specific Aims Investigator Directory 2005 Research Highlights Overview A working definition of "Bioinformatics" is the research, development, and application of computational tools for expanding the use of biomedical data, including methods used to acquire, store, organize, archive, analyze, or visualize such data. Biostatistics is a critical component of this field. This Bioinformatics and Biostatistics Research Core brings together a number of investigators with a wide range of interests falling into the category of bioinformatics who have focused on tackling the myriad issues and problems in this field. The core includes specialists in data integration and presentation, computational algorithms and machine learning, statistical computing, experimental design, biostatistics, proteomics and the proteome, and the practical aspects of the design, analysis, and automating the understanding of gene expression experiments. Examples of critical problems recently addressed by Core investigators include work towards optimal designs for gene expression experiments (Kerr), determination of significance of results by adjusting for multiplicity for large scale hypothesis testing (Storey), combining multiple forms of biological data (Noble, Monks), data integration and knowledge extraction (Tarczy-Hornoch, Samudrala), and informatics and analytics systems development (Tarczy-Hornoch, Samudrala, Rossini). The research that forms the underpinnings of this field span the range of data-centric and analysis-centric areas. Data issues include management, integration, organization, transformation, and placement in context through metadata. Within the domain of biology, these have been recently stressed as critical. Other issues of primary importance statistical analysis issues, including experimental design and statistical modeling; inference and decision making; prediction; and machine learning.

Specific Aims The overall goal of the Bioinformatics and Biostatistics Research Core is to facilitate and foster individual and collaborative research projects aimed at computational and quantitative analysis of biomedical data related to understanding gene/environment interactions. The specific aims for this core are to: Foster collaborative research opportunities among Core investigators through the sharing of complementary quantitative skills to address large scale problems. Enhance the research productivity of Core Investigators via introduction and access to CEEH resources and investigators. Facilitate development of individual research programs addressing a wide range of bioinformatics and biostatistics problems with applications to ecogenetics and environmental health, as well as to broaden the community of quantitative researchers who understand issues related to the Center's mission.