|Herring, Ibrahim, Truong and Zou receive funding from NIH and NSF|
Professor Amy Herring, PhD, has been awarded a five-year grant entitled "Bayesian Methods for High-Dimensional Epidemiologic Data" from the National Institute of Environmental Health Sciences. This project addresses a critical need of finding clues to the etiology and pathogenesis of congenital malformations, using data from the largest population-based study ever conducted on the causes of birth defects.
While birth defects are the leading cause of infant mortality, the leading cause of death among children aged 1-4, and the fifth-ranked cause of premature mortality in the United States, many individual defects are too rare to be studied comprehensively. These new statistical methods incorporate current knowledge of embryonic development and allow some borrowing of information across different birth defects while keeping each defect as a separate entity of interest in the statistical model. These novel methods will allow investigators to investigate the simultaneous influence of multiple exposures and combinations of exposures on multiple outcomes.
Herring leads the research for this project, which includes subcontracts with Duke University and The University of Texas at Austin.
Joseph Ibrahim, PhD, Alumni Distinguished Professor of biostatistics, was recently awarded a competitive
renewal of his project "Bayesian Approaches to Model Selection for Survival Data" from the National Institute of General Medical Sciences. Now in its 13th year, this study aims to develop several novel statistical methods for motif discovery in genomic sequence data. This methodology has major applications in chronic diseases such as cancer, AIDS, cardiovascular disease and environmental health.
Ibrahim is the lead principal investigator, and subcontracts have been awarded to Boston University, The University of Connecticut, and the University of Texas at Austin.
Professor Kinh Truong, PhD, has received funding from the National Science Foundation for a three-year proposal titled "Feature Extraction Involving Multichannel Time Series".
This project has several broad-range impacts. The proposed unified approach provides major insights to the scientific community into the issues related to function estimation in life sciences. This is an essential contribution in the search for better techniques to study the sampling properties of the methods in brain and genomic research. Additionally, the proposed methods will be useful in developing teaching material for a course in statistical fMRI and neural spike train analysis to graduate students. Finally, a much broader health significance of this project will be its contribution to the better understanding of brain diseases.
Associate Professor Fei Zou, PhD, has been awarded funding from the National Institute of General
Medical Sciences for the competitive renewal of her proposal "Robust Methods for Complex Trait mapping with Collaborative Cross".
This project is motivated by a new mouse resource, the Collaborative Cross (CC), and the urgent need for appropriate analytical tools for interpreting new CC data. This proposal not only addresses common analytical challenges encountered with this data, but also identifies unique features of CC projects and develops novel statistical methods to address these unique features.
|Last updated September 20, 2011|