DNA microarray technology, in combination with statistical and predictive modeling tools, could be used to evaluate thousands of genes against distinct gene expression patterns induced by chemical/biological agents to provide early identification and speed therapeutic intervention. The overall objective of this proposal is to demonstrate the feasibility of building a data management system for DNA microarray study data with integrated computational analysis tools that can provide identification of chemical and biological threats on the basis of host gene response. Alpha-Gamma proposes to accomplish these objectives by first building and populating a prototype relational database with several sets of DNA microarray data along with pathological and physiological endpoints. Alpha-Gamma will build a web-based user interface to browse and select data for analysis, and integrate established statistical tools (e.g., SAS, S-Plus, Spotfire, Patek) into this user friendly environment. With this integration of statistical tools, Alpha-Gamma will perform normalization of microarray data sets, cluster analysis, and pattern recognition. Alpha-Gamma will also validate the potential of this approach for identifying unknown agents by reserving known samples from the datasets and applying statistical tools to identify best match and confidence level
