This proposal attempts to address the growing need for integrated gene expression informatics resources in neuroscience. The last five years have seen a rapid increase in the production of gene expression in all areas of biology. Analyzing this wealth of data is becoming more and more complex. While there are public data repositories where raw data can be published, there are few if any efforts to provide advanced analytic capabilities that address the specific needs of neuroscience. We propose to create such a facility that will allow neuroscientists to perform sophisticated computational analyses of large quantities of expression data coming from multiple laboratories. Data submitters will be able to control access to their data and the results coming from their data. The project will involve developing a database for meta-analysis of neuroscience-related gene expression data, tools for submission of data, and tools and algorithms for accessing the database and analyzing the data. Users will be able to perform meta-analyses of differential expression, coexpression (correlated expression), differential coexpression, expression detection, and of expression patterns in functionally-related groups of genes. In addition the system will incorporate other genomics data such as sequences, gene pathways and protein-protein interactions. By linking to and overlaying such data, users will be able to better predict the importance of particular analysis results. Finally, we will develop methods to incorporate domain-specific data into gene expression microarray analyses, such as neuroanatomy, neural connectivity and brain in situ hybridizations. This project will enable future collaborative efforts to target specific diseases or processes for examination.
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