A web platform for integrative genomic analysis in aging

University Of Southern California, Los Angeles CA

Investigators

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Abstract

DESCRIPTION (provided by applicant): The recent development of high-throughput technologies generated enormous genomic data to understand the genetic basis of aging. For example, more than eighty microarray studies have directly addressed aging-related expression patterns in diverse model organisms and under different conditions. However, efficient exploitation of this vast amount of microarray data is frustrated by the lack of bioinformatics resources to enable convenient cross-laboratory searches of primary array signals. We have develop the web-database Gene Aging Nexus (GAN) freely accessible to the biogerontological-geriatric research community to query/analyze/visualize various aging-related genomic data sources, in particular, microarray data. In this proposal, we will continue the development of GAN. In particular, (1) We will expand the central web database for aging microarray data of six species: human (H. sapiens), rat (R. norvegicus), mouse (M. musculus), `fly'(D. melanogaster), `worm'(C. elegans), and yeast (S. cerevisiae). (2) We will implement a set of novel tools for cross-platform microarray data integration and analysis, and also implement useful methods reported in the literature. (3) We will incorporate other genomic data sources, such as biological pathways, transcription regulation, protein-protein interactions, genome sequences, and literature knowledge. By integrating such data, users will be able to better understand and interpret the results derived from array analysis, to assign unknown genes to aging-related pathways, and to predict transcriptional regulation. GAN could help launch the next phase of evaluating possible universals in aging-related gene expression in tissues of diverse organisms. The construction of the GAN platform and the associated analysis of a large number of public aging genomic data could constitute one of the largest bioinformatics undertakings in aging research. GAN could help launch the next phase of evaluating possible universals in aging-related gene expression in tissues of diverse organisms, and facilitates the systems understanding of aging.