Bayesian Computation in Systems and Synthetic Biology
Bayesian Computation in Systems and Synthetic Biology
批准号:
EP/J020281/1
负责人:
David Wild
金额:
$6.29万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2013
资助国家:
英国
项目状态:
已结题
起止时间:
2013 至 --
中文摘要
该提案要求支持访问南加州大学基因组科学卓越中心(CEGS)和加州理工学院(马约实验室),以交流思想,开发新的研究路线并探索合作企业。将这些访问联系起来的基本科学主题是开发贝叶斯统计建模的先进工具,并将其应用于系统和合成生物学中的两个具有挑战性的问题-理解遗传变异和设计新型蛋白质分子。这一提议超越了传统的学术学科界限,处于生物物理学、基因组学和计算生物学的交界处。现代系统生物学方法的一个关键特征是旨在将数学和统计建模与当代细胞和分子数据的巨大数量和多样性联系起来,例如来自高通量、全基因组和成像技术的数据。现代生物学和医学面临的最重要的挑战之一是了解个体之间的遗传变异(基因型)如何转化为我们可以看到或测量的变异类型,例如血压(表型),以及环境如何影响这种关系。虽然近年来在鉴定各种生物体中的调控基因和模块方面取得了相当大的进展,但对下游基因调控网络以及这些网络中的变化如何导致表型差异以及如何反过来受环境影响的知识仍然有限。由Simon Tavare FRS教授领导的南加州大学基因组科学卓越中心(CEGS)是美国国立卫生研究院资助的仅有的11个CEGS之一,重点是利用现代基因组学技术产生的异质数据来了解遗传变异。Tavare教授因其在统计学,概率学以及生物和医学科学的界面上的工作而受到国际认可。他对组合随机过程、群体遗传学和统计生物信息学的研究做出了重要贡献。对CEGS的访问将提供一个无与伦比的机会,与广泛的研究人员进行互动,包括分子生物学家,人口遗传学家,遗传流行病学家,统计学家,计算机科学家和数学家,他们专注于这些问题。虽然系统生物学试图理解生物过程的设计原则,但合成生物学试图将这种理解应用于设计和构建自然界中未发现的新生物功能和系统。合成生物学的一个方面是蛋白质设计,其中我们对蛋白质结构和功能的基本原理的理解正在应用于现有蛋白质的重新设计或新蛋白质的设计。Steve马约教授是蛋白质设计领域的先驱之一,也是美国国家科学院的成员;他在加州理工学院的实验室的重点是使用理论,计算和实验方法来研究结构生物学,特别是开发蛋白质设计的定量方法。加州理工学院在2011- 2012年泰晤士高等教育全球排名前200名大学中被评为世界第一大学。对马约教授实验室的访问将提供一个独特的机会,与广泛的研究人员进行互动,这些研究人员将理论,计算和实验方法应用于蛋白质设计,蛋白质序列进化和蛋白质-蛋白质识别的研究,在世界一流的环境中。
英文摘要
This proposal is to request support for visits to the Centre of Excellence in Genomic Sciences (CEGS) at the University of Southern California, and Caltech (Mayo Laboratory), to exchange ideas, develop new lines of research and explore collaborative ventures. The underlying scientific theme which links these visits is the development of advanced tools for Bayesian statistical modelling, and their application to two challenging problems in systems and synthetic biology - the understanding of genetic variation and the design of novel protein molecules. This proposal surmounts traditional academic disciplinary boundaries and lies at the interface of biophysics, genomics and computational statistics.A key feature that distinguishes the modern approach to systems biology is the aim of linking mathematical and statistical modelling with the huge volume and diversity of contemporary cellular and molecular data, such as that coming from high-throughput, genome-wide and imaging technologies. One of the most important challenges facing modern biology and medicine is to understand how the genetic variation between individuals (the genotype) translates into the type of variation we can see or measure, such as blood pressure (the phenotype), and how environment influences this relationship. Although considerable progress has been made in recent years in identifying regulatory genes and modules in various organisms, there is still limited knowledge about downstream gene regulatory networks, and about how variation in these networks results in phenotypic differences, and is, in turn, affected by the environment. The Centre of Excellence in Genomic Sciences (CEGS) at the University of Southern California, directed by Professor Simon Tavare FRS, is one of only 11 CEGS funded by the National Institutes of Health, with a focus on the use of the heterogeneous data produced by modern genomics technologies to understand genetic variation. Professor Tavare is internationally recognised for his work at the interface of statistics, probability and the biological and medical sciences. He has made important contributions to the study of combinatorial stochastic processes, population genetics and statistical bioinformatics. The visit to CEGS will provide an unparalleled opportunity to interact with a wide range of researchers, including molecular biologists, population geneticists, genetic epidemiologists, statisticians, computer scientists, and mathematicians, who are focused these problems. Whilst systems biology attempts to understand the design principles underpinning biological processes, synthetic biology attempts to apply this understanding to the design and construction of novel biological functions and systems not found in nature. One facet of synthetic biology is protein design, in which our increasing understanding of the principles underlying protein structure and function is being applied in the redesign of existing proteins, or the design of novel proteins. Professor Steve Mayo is one of the pioneers of the field of protein design and a member of the US National Academy of Sciences; the focus of his laboratory at Caltech is the use of theoretical, computational, and experimental approaches to study structural biology, and in particular to develop quantitative methods for protein design. Caltech was rated the world's number one university in the 2011--2012 Times Higher Education global ranking of the top 200 universities. The visit to Professor Mayo's laboratory will provide a unique opportunity to interact with a wide range of researchers applying theoretical, computational, and experimental approaches to the study of protein design, protein sequence evolution and protein-protein recognition, in a world-class environment.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1016/j.cpc.2015.12.005
发表时间:
2016-04-01
期刊:
COMPUTER PHYSICS COMMUNICATIONS
影响因子:
6.3
作者:
[Burkoff, Nikolas S., Baldock, Robert J. N., Csanyi, Gabor]
通讯作者:
Csanyi, Gabor
DOI:
10.1371/journal.pone.0169356
发表时间:
2017
期刊:
PloS one
影响因子:
3.7
作者:
[Várnai C, Burkoff NS, Wild DL]
通讯作者:
Wild DL
Bayesian modelling for developmental systems biology
-
批准号:EP/R014337/1
-
项目类别:Research Grant
-
资助金额:$6.27万
-
财政年份:2017
-
负责人:David Wild
-
依托单位:
iPlant UK
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批准号:BB/M018431/1
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项目类别:Research Grant
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资助金额:$226.32万
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财政年份:2015
-
负责人:David Wild
-
依托单位:
Collaborative Research: Cheminformatics OLCC
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批准号:1140146
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项目类别:Standard Grant
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资助金额:$4.5万
-
财政年份:2012
-
负责人:David Wild
-
依托单位:
Managing the Data Explosion in Post-Genomic Biology with Fast Bayesian Computational Methods
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批准号:EP/F027400/1
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项目类别:Research Grant
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资助金额:$33.63万
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财政年份:2008
-
负责人:David Wild
-
依托单位:
BioCmp: Reconstructing Metabolic and Transcriptional Networks using Bayesian State Space Models
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批准号:0524331
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项目类别:Continuing Grant
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资助金额:$0.0万
-
财政年份:2005
-
负责人:David Wild
-
依托单位:
国内基金
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