Mprime Research Project
Dr. Shelley Bull,
Research Expertise: Statistical genetic methods, Multivariate statistical modeling of categorical outcomes, Statistical methods for microarray data, Models for family data, Generalized linear models, Resampling methods
Complex traits, such as susceptibility to diabetes, cancer or tuberculosis, that vary in human and natural populations are determined by multiple genetic and environmental factors that interact with one another in complicated ways. The nature and complexity of these interactions depend on characteristics of the population as well as characteristics of the individual and the family. With continuing advances in molecular biologic technology and the availability of a complete reference sequence of the entire human genome, investigators must deal with data that have high dimension and complex structure. Appropriate analysis is required to direct scientific and economic energy and resources into feasible and effective interventions.
Our research will assist in the discovery and characterization of the genes that influence disease susceptibility, and lead to a better understanding of how genes function and the subsequent development of new approaches to the diagnosis and treatment of common diseases. Characterization of the joint influences of genetic and environmental factors on disease is essential to the development of population interventions to prevent disease and in health care planning. The developments being made to address current problems in forest genetics of natural populations contribute to the understanding of forestry conservation genetics, as well as to general problems in statistical genetics.