REU Site: Modeling and Simulation in Systems Biology
REU Site: Modeling and Simulation in Systems Biology
批准号:
1062878
负责人:
Sallie Keller
金额:
$38.62万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-04-15 至 2015-09-30
中文摘要
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英文摘要
The objective of the proposed program is to provide a 10-week residential summer research experience in mathematical biology to undergraduate students from around the U.S. and Puerto Rico, with the goal of increasing their desire and preparation to enter a Ph.D. program in mathematics or computational biology. The students will be mentored by faculty from the Virginia Bioinformatics Institute (VBI) and the Wake Forest University School of Medicine in Winston-Salem, NC. They will participate in research projects in two related areas: Modeling of mammalian intracellular iron metabolism in two cell types, as well as a multiscale model connecting the intracellular and the systemic scales; and construction and implementation of mathematical algorithms for the analysis of biological networks. These algorithms will be used to study models of iron metabolism. It is widely recognized that mathematical tools are indispensable for the understanding of biological networks and their dynamic properties. The proposed program involves students in research projects that model biological networks with mathematical tools. The students will develop the tools as well as apply them. The projects are carried out in close collaboration with experimental scientists. The program will prepare a total of 36 undergraduates for the challenges of modern interdisciplinary quantitative life sciences research. It will motivate them to enter a Ph.D. program and will help them be successful in their graduate career. Particular emphasis in recruiting will be placed on the inclusion of members from underrepresented groups. Thus, the program will contribute to the recruitment and training of a highly specialized workforce at the interface of experiment and computation, responding to the ever-growing need for experts that can apply quantitative methods to life science and biomedical research.
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