Project Description: Specific Aims: The long-term goal of this work is 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. Specifically, this project advances our prior work that resulted in an integrated knowledge base of the biological (genetic) basis of Alzheimers Disease pathology, incorporating current knowledge from the literature, the AlzGene Database, and other sources, which can be dynamically updated as new information is published and directly via investigator suggestion. We completed a simple interface that allows researchers to access this data. The aims of the present work are to 1) enable the program to dynamically integrate data resulting from empirical assays, particularly microarray expression data and GWAS data, to the database, 2) add functional and other relationship annotations for each gene that might be relevant to the researcher (pathway, gene-disease, gene-function, and gene-drug), and 3) add a gene prioritization and scoring module, which would offer, for each of the suggested genes, a quantitative score that reflects the strength of the evidence for each genes association with Alzheimers Disease. The outcomes of these aims will be validated with expert analysis (Huentelman and Caselli) of the resulting selection of targets. Further empirical validation (such as qrtPCR and immunohistochemistry) of any target of interest will be pursued with collaborators under separate funding, at their discretion.
|Effective start/end date||9/16/13 → 6/30/14|
- HHS-NIH: National Institute on Aging (NIA): $153,000.00
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