Driven by initiatives such as the Human Genome, ENCODE, HapMap, and 1000 Genomes Projects, genetics and genomics have taken a central role in the biomedical sciences. In the same way, advances in computation are driving the mathematical sciences forward. These factors, the increasingly quantitative nature of biomedical research, and the explosive growth of genetic and genomic data have resulted in a continually increasing demand for individuals trained at the interface of genetics, genomics, and the mathematical sciences. Recognizing this demand, the NHGRI and NIGMS in spring 2008 convened a workshop focused on """"""""Research Training Needs in Statistical Genetics and Genetic Epidemiology."""""""" Participants affirmed the existence of a key need, stating """"""""there is not a sufficiently trained cadre of scientists to develop methods and analyze the vast amount of data generated from population genomics studies employing current and rapidly emerging technologies."""""""" The continuing goal of the University Of Michigan Genome Science Training Program (GSTP) is to fill this need by training pre- and postdoctoral trainees at the interface of genetics, genomics, and the mathematical sciences, with particular emphasis on training statistical human geneticists, and human molecular geneticists with a strong grounding in statistics and the mathematical sciences. The GSTP is based in the participating departments of Biostatistics, Human Genetics, and Epidemiology;with other participating faculty come from Ecology and Evolutionary Biology and Statistics. The fundamental premise of the GSTP is that graduates should have substantial training in the mathematical and biological sciences and at their interface. Such training facilitates communication between disciplines, identification of important problems, and identification of the mathematical and computational tools required to solve those problems. We request support for seven predoctoral trainees and three postdoctoral trainees. Trainees will be supported for two to three years to provide time for the interdisciplinary training we have demonstrated as critical to their success. Graduates of the GSTP will continue to help fill the need for statistical geneticists and genome scientists, and in so doing, help the NHGRI achieve its goals of translation of DNA sequence and annotation information into advances in our understanding of the genetic basis of human health and disease.

Public Health Relevance

This proposal seeks continued funding for the University of Michigan Genome Science Training Program (GSTP). The goal of the GSTP is to train doctoral students and post-doctoral fellows at the interface of the mathematical sciences and human genetics, a critical area of genome science in which well trained individuals are in high demand and short supply.

National Institute of Health (NIH)
National Human Genome Research Institute (NHGRI)
Institutional National Research Service Award (T32)
Project #
Application #
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Graham, Bettie
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Michigan Ann Arbor
Biostatistics & Other Math Sci
Schools of Public Health
Ann Arbor
United States
Zip Code
Nishizaki, Sierra S; Boyle, Alan P (2017) Mining the Unknown: Assigning Function to Noncoding Single Nucleotide Polymorphisms. Trends Genet 33:34-45
Metzger, Brian P H; Wittkopp, Patricia J; Coolon, Joseph D (2017) Evolutionary Dynamics of Regulatory Changes Underlying Gene Expression Divergence among Saccharomyces Species. Genome Biol Evol 9:843-854
McConnell, Michael J; Moran, John V; Abyzov, Alexej et al. (2017) Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network. Science 356:
Camper, Sally A; Daly, Alexandre Z; Stallings, Caitlin E et al. (2017) Hypothalamic ?-Catenin Is Essential for FGF8-Mediated Anterior Pituitary Growth: Links to Human Disease. Endocrinology 158:3322-3324
Duveau, Fabien; Yuan, David C; Metzger, Brian P H et al. (2017) Effects of mutation and selection on plasticity of a promoter activity in Saccharomyces cerevisiae. Proc Natl Acad Sci U S A 114:E11218-E11227
Kopera, Huira C; Flasch, Diane A; Nakamura, Mitsuhiro et al. (2016) LEAP: L1 Element Amplification Protocol. Methods Mol Biol 1400:339-55
Zeng, Chenjie; Matsuda, Koichi; Jia, Wei-Hua et al. (2016) Identification of Susceptibility Loci and Genes for Colorectal Cancer Risk. Gastroenterology 150:1633-1645
Metzger, Brian P H; Duveau, Fabien; Yuan, David C et al. (2016) Contrasting Frequencies and Effects of cis- and trans-Regulatory Mutations Affecting Gene Expression. Mol Biol Evol 33:1131-46
Moyers, Bryan A; Zhang, Jianzhi (2016) Evaluating Phylostratigraphic Evidence for Widespread De Novo Gene Birth in Genome Evolution. Mol Biol Evol 33:1245-56
Zhang, Yanxiao; Koneva, Lada A; Virani, Shama et al. (2016) Subtypes of HPV-Positive Head and Neck Cancers Are Associated with HPV Characteristics, Copy Number Alterations, PIK3CA Mutation, and Pathway Signatures. Clin Cancer Res 22:4735-45

Showing the most recent 10 out of 121 publications