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.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Institutional National Research Service Award (T32)
Project #
5T32HG000040-19
Application #
8502275
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Junkins, Heather
Project Start
1995-07-01
Project End
2015-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
19
Fiscal Year
2013
Total Cost
$727,914
Indirect Cost
$42,068
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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
Moyers, Bryan A; Zhang, Jianzhi (2016) Evaluating Phylostratigraphic Evidence for Widespread De Novo Gene Birth in Genome Evolution. Mol Biol Evol 33:1245-56
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 150:1633-45
Moyers, Bryan A; Zhang, Jianzhi (2015) Phylostratigraphic bias creates spurious patterns of genome evolution. Mol Biol Evol 32:258-67
Virani, Shama; Bellile, Emily; Bradford, Carol R et al. (2015) NDN and CD1A are novel prognostic methylation markers in patients with head and neck squamous carcinomas. BMC Cancer 15:825
Demanelis, Kathryn; Sriplung, Hutcha; Meza, Rafael et al. (2015) Differences in childhood leukemia incidence and survival between Southern Thailand and the United States: a population-based analysis. Pediatr Blood Cancer 62:1790-8
Stenzel, Stephanie L; Ahn, Jaeil; Boonstra, Philip S et al. (2015) The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification. Eur J Epidemiol 30:413-23
Schumacher, Fredrick R; Schmit, Stephanie L; Jiao, Shuo et al. (2015) Genome-wide association study of colorectal cancer identifies six new susceptibility loci. Nat Commun 6:7138
Darr, Owen A; Colacino, Justin A; Tang, Alice L et al. (2015) Epigenetic alterations in metastatic cutaneous carcinoma. Head Neck 37:994-1001

Showing the most recent 10 out of 114 publications