Grants are awarded to Old Dominion University and to Eastern Virginia Medical School in order to develop novel computational methods for analyzing the Allen Brain Atlas data set, which contains the most comprehensive collection of genome-scale, cellular-resolution, three-dimensional gene expression patterns of the mouse brain. Global analyses of these data would elucidate the anatomic and genetic landscapes of the mammalian brain, leading ultimately to the understanding of brain functional circuitry. This project will develop a class of novel computational methods for integrative analysis of the anatomic and genetic landscapes in the mouse brain. To enable genome-wide global computation, this project will investigate hierarchical models for incorporating genome-wide and brain-wide structures. Additionally, tensor computation techniques will be developed for data compression and visualization. Insights obtained through the application of advanced computational methods as proposed here have the potential to enable and accelerate biological insights and generate experimentally testable hypotheses. In particular, this project is expected to enable significant progress in the areas of (1) understanding the structure and development of the mammalian brain through the multidimensional analysis of genetic networks that can be identified through systems-level analysis of gene expression, (2) understanding molecular pathways that are active and contribute to the function of the mammalian brain, and (3) understanding how disruptions of genes and thus molecular pathways might contribute to pathologies of mouse and ultimately human brains.
The project will play an integral part in educating and training students. The Allen Brain Atlas resources have been integrated into undergraduate and graduate curricula as appealing pedagogical tools. This project will go beyond the raw data by extracting new knowledge from them, thereby significantly enriching current curricula and catalyzing new course development. The anatomic and genetic connectivity maps will be used as innovative pedagogical tools, where they offer visually appealing aids and examples for teaching a variety of topics and provide opportunities for in silico laboratory exercises. The educational activities will leverage Old Dominion University's top-class distance learning program whose sites are specifically designed to serve people with limited educational resources. For more information please visit the project website at http://compbio.cs.odu.edu/NSF-ABI/.
