Arizona Alzheimer's Disease Core Center Arizona Alzheimer's Disease Core Center Many methods have been proposed for facilitating the uncovering of genes that underlie the pathology of different diseases using data from targeted experiments that measure gene expression levels under specific conditions or analyze SNPs over the whole genome (GWAS). Some are purely statistical, resulting in a (mostly) undifferentiated set of genes that are differentially expressed (or co-expressed), while others seek to prioritize the resulting set of genes through comparison against specific known targets. We address the specific problem faced by scientists when analyzing the results from high throughput experiments, trying to pinpoint key sets of genes among thousands for further, focused, empirical validation. Considering that empirical validation of even a single causative gene is a long and expensive process, trimming down the list of potential gene targets to a manageable size that includes the most significant prospects for further validation is clearly a critical problem. We propose to move beyond purely statistical and comparative methods for gene target selection, and advance towards a richer model of discovery based on the integration of multiple knowledge and data sources. The method will use selected data from microarray and GWAS assays along with topological analysis of protein interaction and gene ontology networks for the guided discovery of potential therapeutic targets that underlie the pathology of Alzheimers Disease. The ranking methodology proposed has solid biological and mathematical basis and has been shown to be at least as accurate as the best ranking system currently available to researchers, but with capacity to allow novel hypothesis (gene targets) among the top rankings.
|Effective start/end date||7/1/11 → 6/30/12|
- Arizona Alzheimer's Consortium: $125,000.00
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