Description :  The enhanced capacity to computationally interpret gene expression experiments in cell physiology and pharmacology will help ease the global health care burdens caused by the combination of increased disease and increased drug costs. While gene array experiments increase, discoveries of automated discovery routines have lagged. Molecular diagnostics using data mining methods offer the promise of precise, objective, systematic, and reliable disease diagnostics and drug treatment.  Novel data mining technologies in support of the scientific and economic development of the state of Louisiana and the nation are the focus of this project, including research and development of efficient and robust algorithms data preparation, dimensionality and noise reduction, normalization, unsupervised classification, and functional interpretation of gene expression data.  Researchers will reach a fundamental understanding regarding the intricate processes involved in data cleaning, preprocessing, spatial data structure, and algorithm design, parameter estimation, and functional interpretation of mining results. In this endeavor, both graduate and undergraduate students are extensively involved, gaining a comprehensive research experience in a multi-disciplinary and multi-institutional setting, and obtaining the knowledge and experience they need for continued future professional development.  This fundamental research, besides yielding important computing research results, enhances collaborative research and mentoring relationships with established researchers from LSU Health Sciences Center, New Orleans.

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Principal Investigator:  Dua, Sumeet  --  Computer Science

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Collaborators:  

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Funding Agencies:  Board of Regents

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Amount Awarded:  $70,172

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Start Period:  06/01/2005

End Period:  06/30/2006