Description :  Continued research and development of gene expression data normalization, dimensionality reduction, supervised and unsupervised classification, and functional interpretation of gene expression data are the focus of this project. A fundamental understanding will also be reached of the intricate processes involved in the data cleaning, preprocessing, parameter estimation, and functional interpretation of the results. The project provides research experience for both undergraduate and graduate students, and supports the mission of the Bioinformatics core of Louisiana Biomedical Research Network and the scientific and economic development of the State of Louisiana. This project enables fundamental research and develops collaborative research and mentoring relationships with established researchers from LBRN member institutions. Our preliminary results have clearly suggested that correlation determination techniques such as association rule discovery, approximate entropy estimation, and singular spectrum analysis hold much promise for precise and accurate analysis of gene expression data for physiological discovery. Two goals of this project are the maturation of these ideas to completion and the motivation to develop planned publications and a research proposal to a federal agency in this area.

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Principal Investigator:  Dua, Sumeet  --  Computer Science

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Collaborators:  

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Funding Agencies:  NIH through LSU

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Amount Awarded:  $121,253

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Start Period:  06/01/2004

End Period:  06/30/2005