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Genomics & Computational Biology: an REU Site

Genomics & Computational Biology: an REU Site
基因组学
批准号:
0243754
负责人:
Jonathan Arnold
金额:
$21.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-03-01 至 2008-02-29

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中文摘要
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英文摘要
Hands-on research in Genomics and Computational Biology will bring 10 participants recruited nationally from underrepresented groups to UGA, where they will interact with an established interdisciplinary team working on identifying biological circuits for fundamental processes and validating these biological circuits by fitting them to genomics data. Since the discovery of DNA as the genetic material 60 years ago, biologists have been taking apart living systems on a finer and finer scale until we have been able to determine the complete genetic blueprint of many organisms. The challenge of the new millennium is "reassembling the pieces", i.e., moving from genomes to life. One approach to reassembling the pieces is to borrow a metaphor from computer science: the entire chemical reaction network describing what a cell does is a biological circuit. The theme for this genomics and computational biology program is "computing life", i.e., identifying biological circuits for fundamental processes like carbon metabolism and validating these biological circuits by fitting them to genomics data describing what the cell is doing (i.e., RNA and protein profiling data) (PNAS 99: 16904-16909 (2002)). For more information contact lindalee@uga.edu or visit http://gene.genetics.uga.edu/stc. This site is supported by the Department of Defense in partnership with the NSF REU program
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会议论文
Collective Behavior of Cellular Oscillators
RAPID: finding virulence genes as therapeutic targets in Covid-19
Gordon Research Conference on Collective Behavior
  • 批准号:
    2026268
  • 项目类别:
    Standard Grant
  • 资助金额:
    $3.0万
  • 财政年份:
    2020
  • 负责人:
    Jonathan Arnold
  • 依托单位:
Measuring and Modeling How Clocks in Single Cells Communicate: an interdisciplinary apporach
国内基金
海外基金
Computational Methods for Analyzing Toponome Data