Research Training in Mental Health Epidemiology
The goal of this T32 training program is to provide rigorous training in the application of epidemiologic and statistical methods to psychosocial and psychiatric research. Formal training, mentorship, and extensive research experience will provide trainees with the requisite methodological and substantive tools to conduct high quality research in mental health. Providing exposure to diverse specialty areas both within and among the current program and other ongoing training initiatives will provide a broad perspective on the substantive areas of psychiatric research and appreciation of the need for a multidisciplinary approach that is critical to understanding pathogenesis and the impact of mental disorders.
Analysis of Genomic Data for Complex Traits
The goal of this R01 project is to develop statistical tools and analytic methods to enhance our understanding of complex phenotypes such as cocaine and nicotine dependence, by developing novel statistical methods. These methods will be used for unraveling the genetic basis of complex disorders. Specifically, the goal is to develop, evaluate and apply new statistical models, methods and software to conduct genetic analyses of complex traits. Of particular interest are ordinal traits, as methods and software virtually do not exist.
Data management, statistics, and informatics core
This U01 award is to establish a data management, statistics, and informatics core at Yale University as a part of the National Genomic and Proteomic Network for Preterm Birth Research. It will be responsible for the central database, data analysis, and management; information technology and coordination of the administrative activities of the Network. As part of this network, this program will be responsible for:
- Establishing and maintaining a central database, data analysis, and information technology.
- Collaboration with investigators in the three clinical cores to define the study hypotheses and play a leadership role in the study design.
- Interaction with investigators in the analytic core for analyzing genomic and proteomic data.
- Establishing and maintaining a public, web-based, genomic and proteomic database for data mining and data deposition by the research community as well as within the network.