EAGER: Algorithms for Synthetic Gene Library Design
EAGER:合成基因库设计算法
基本信息
- 批准号:1418874
- 负责人:
- 金额:$ 20万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-10-01 至 2017-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Introduction/Motivation: Synthetic Biology moves beyond conventional genetic manipulation to construct novel biological components which do not originate in nature. There still exists though a big gap of knowledge between genomic sequence and function. To enhance understanding of gene expression, researchers have constructed and evaluated libraries of gene variants, which traditionally have limited size due to synthesis costs, and random or biased composition. Valuable insights have been gained, but precise control of expression in redesigned synthetic genes remains elusive.The proposed algorithmic research involves combinatorial design of synthetic gene variants to aid the construction of large scale, purposed libraries. The aim is to assay the most important sequence features which determine gene expression, while minimizing experimental cost and maximizing the exploration of the coding landscape. Proposed design, synthesis and wet-lab evaluation of reporter gene variants with modified characteristics will help determine their quantitative effect on expression in a model organism and validate our algorithmic designs.Intellectual merit: Upon successful completion, this project will make major advances in the computational and life sciences, through new algorithmic results in combinatorial design of diverse gene libraries with minimized cost, and fundamental discoveries regarding gene expression. PIs expect their design methodologies to fuel an array of new discoveries by enabling high throughput cost effective experiments to study the effects of sequence features of genes and pathways, and help gain important insights by comparing experimental observations with long standing computational and theoretical models.Broader Impact: The algorithms and software developed with this award will be used to design the next generation of large-scale synthetic construct experiments, which will enable optimized redesign of genetic elements to be transferred from one organism to another, adapting to an altogether different environment. The primary impact will ultimately rest with the science done using these techniques, such as drug and chemical synthesizing microorganisms with improved yields, rapidly produced vaccines, and CO2 transforming micro-algae. The educational impact includes active promotion of computational and synthetic biology in lectures towards graduate and undergraduate students, and dissemination of research findings and data through web accessible repositories.
简介/动机:合成生物学超越了传统的遗传操作,构建了非自然界来源的新生物成分。基因组序列与功能之间存在着巨大的知识鸿沟。为了增强对基因表达的理解,研究人员构建并评估了基因变体库,这些基因变体库由于合成成本以及随机或有偏见的组成而传统上具有有限的大小。虽然已经获得了一些有价值的见解,但在重新设计的合成基因中精确控制表达仍然是一个难题,所提出的算法研究涉及合成基因变体的组合设计,以帮助构建大规模的有目的的文库。其目的是分析决定基因表达的最重要序列特征,同时最大限度地降低实验成本并最大限度地探索编码景观。所提出的具有修饰特征的报告基因变体的设计、合成和湿实验室评估将有助于确定它们对模型生物中表达的定量影响,并验证我们的算法设计。成功完成后,该项目将在计算和生命科学方面取得重大进展,通过以最小成本组合设计不同基因文库的新算法结果,和基因表达的基本发现。PI希望他们的设计方法能够通过高通量的成本效益实验来研究基因和通路的序列特征的影响,从而推动一系列新发现,并通过将实验观察结果与长期存在的计算和理论模型进行比较来帮助获得重要的见解。该奖项开发的算法和软件将用于设计下一代大规模合成构建实验,这将使遗传元件的优化重新设计能够从一个生物体转移到另一个生物体,以适应完全不同的环境。主要影响最终将取决于使用这些技术所做的科学,例如提高产量的药物和化学合成微生物,快速生产疫苗和二氧化碳转化微藻。教育影响包括在面向研究生和本科生的讲座中积极推广计算和合成生物学,以及通过网络访问存储库传播研究成果和数据。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Dimitris Papamichail其他文献
Extracting DICOM metadata from PACS recursively over local network
- DOI:
10.1016/j.ejmp.2016.07.141 - 发表时间:
2016-09-01 - 期刊:
- 影响因子:
- 作者:
Dimitris Papamichail;Agapi Ploussi;Sofia Kordolaimi;Ioannis Saradeas;Nikolaos L. Kelekis;Efstathios P. Efstathopoulos - 通讯作者:
Efstathios P. Efstathopoulos
Review of design theory by C. C. Lindner and C. A. Rodger
- DOI:
10.1145/2160649.2160662 - 发表时间:
2012-03 - 期刊:
- 影响因子:0
- 作者:
Dimitris Papamichail - 通讯作者:
Dimitris Papamichail
Improved algorithms for approximate string matching (extended abstract)
- DOI:
10.1186/1471-2105-10-s1-s10 - 发表时间:
2009-01-30 - 期刊:
- 影响因子:3.300
- 作者:
Dimitris Papamichail;Georgios Papamichail - 通讯作者:
Georgios Papamichail
Dimitris Papamichail的其他文献
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{{ truncateString('Dimitris Papamichail', 18)}}的其他基金
EAGER: Algorithms for Synthetic Gene Library Design
EAGER:合成基因库设计算法
- 批准号:
1348275 - 财政年份:2013
- 资助金额:
$ 20万 - 项目类别:
Standard Grant
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