CAREER: Computational and Statistical Genomics of Gene Families
CAREER: Computational and Statistical Genomics of Gene Families
批准号:
0845494
负责人:
Matthew Hahn
金额:
$100.33万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-07-01 至 2014-06-30
中文摘要
(该奖项由《2009年美国复苏和再投资法案:公法111-5》提供资金)。这是一个职业奖项,旨在支持马修·哈恩博士在印第安纳大学生物系和信息学学院的研究。哈恩博士是一名三年级终身教职助理教授。基因组测序项目揭示了物种之间基因家族大小的巨大而频繁的变化。这些变化被证明是物种之间形态、生理和行为差异的原因,并对我们在自然界中观察到的大部分遗传和基因组多样性做出了贡献。为了进一步理解这些变化的重要性,研究人员必须能够理解基因家族进化的机制和模式。尽管关于基因家族的数据越来越多,但直到最近,我们还缺乏一个统计框架来推断基因家族在物种之间的进化。在他的论文研究的早期工作中,哈恩博士提出了这样一个研究基因家族进化的框架,并表明它可以用于假设检验、祖先状态的推断以及基因复制和缺失率的估计。该项目将开发新的统计和计算方法来研究基因家族,并研究基因家族进化的生物学机制。这项工作使得能够更精确地估计基因复制和丢失率,并将为检测和研究全基因组复制提供新的方法。还将开发从低覆盖率基因组中研究基因家族的方法。基因复制可以将类似的基因分布在整个基因组中。单个基因的位置将允许研究基因家族的基因组内和基因组间的动力学。血统的基因周转率不同,这就提出了一个问题,即这些差异是如何产生的。这项研究正在确定决定不同谱系和不同基因家族之间观察到的比率差异的生物学因素。哈恩博士正在开发新的计算模型和自由软件,这些软件将在http://www.bio.indiana.edu/~hahnlab/.This研究会议上提供,将有助于许多领域,包括基因和基因组复制的研究,以及基因调控、转座元件、遗传稳健性和核糖核酸干扰的研究。作为他职业项目的一部分,PI正在整合高中、本科生和研究生等不同领域的知识,为生物推理提供信息,并创造新的科学探究路线。此外,PI将为当地一所以技术为重点的高中的学生准备和实施一门课程。本课程将通过介绍编程的基本原理和生物学的基本原理,将计算机整合到生物课堂中。
英文摘要
(This award is funded through the American Recovery and Reinvestment Act of 2009: Public Law 111-5).This is a CAREER award to support the research of Dr. Matthew Hahn in the Department of Biology and School of Informatics at Indiana University. Dr. Hahn is a third-year, tenure-track Assistant Professor. Genome sequencing projects have revealed large and frequent changes between species in the size of gene families. These changes have been shown to be responsible for morphological, physiological, and behavioral differences between species, and to contribute to much of the genetic and genomic diversity we observe in nature. To further understand the importance of these changes, researchers must be able to understand the mechanisms and modes by which gene families evolve. Despite the growing body of data on gene families, until recently we lacked a statistical framework that would allow for inferences regarding gene family evolution among species. In earlier work from his dissertation research, Dr. Hahn proposed such a framework for studying gene family evolution, and showed that it could be used for hypothesis testing, inference of ancestral states, and estimation of gene duplication and deletion rates. This project will be developing novel statistical and computational methods for studying gene families, and examining the biological mechanisms underlying gene family evolution. This work is enabling more refined estimates of gene duplication and loss rates, and will provide new ways for detecting and studying whole genome duplications. Methods for studying gene families from low-coverage genomes will also be developed. Gene duplication can distribute paralogous genes across the genome. Locations of individual genes will allow study of both within-genome and between-genome dynamics of gene families. Lineages differ in their rates of gene turnover which raises the question of how these differences come about. This research is identifying the biological factors determining observed rate variation among lineages and among individual gene families. Dr. Hahn is developing new computational models and free software, which will be available at http://www.bio.indiana.edu/~hahnlab/.This research will contribute to many fields, including studies of gene and genome duplication to studies of gene regulation, transposable elements, genetic robustness, and RNA interference. As a part of his CAREER project, the PI is integrating knowledge from these diverse fields at high school, undergraduate, and graduate levels to inform biological reasoning and to create new lines of scientific inquiry. Further, the PI will prepare and implement a curriculum for students at a local technology-focused high school. This curriculum will integrate computers into the biology classroom by introducing the basic principles of programming alongside the basic principles of biology.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
CAGEE: Computational analysis of gene expression evolution
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批准号:2146866
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项目类别:Standard Grant
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资助金额:$89.25万
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财政年份:2022
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负责人:Matthew Hahn
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依托单位:
Evolutionary inference in the presence of gene tree discordance
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批准号:1936187
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项目类别:Standard Grant
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资助金额:$64.0万
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财政年份:2020
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负责人:Matthew Hahn
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依托单位:
ABI Development: CAFE for very large comparative genomic datasets
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批准号:1564611
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项目类别:Standard Grant
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资助金额:$79.43万
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财政年份:2016
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负责人:Matthew Hahn
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依托单位:
EAGER: Genome construction in non-model organisms using recombinant populations
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批准号:1249633
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项目类别:Continuing Grant
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资助金额:$25.39万
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财政年份:2012
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负责人:Matthew Hahn
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依托单位:
Comparative Genomics of Gene Family Evolution
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批准号:0528465
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项目类别:Standard Grant
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资助金额:$5.0万
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财政年份:2006
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负责人:Matthew Hahn
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依托单位:
Statistical and Computational Methods for the Study of Gene Families
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批准号:0543586
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项目类别:Standard Grant
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资助金额:$36.02万
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财政年份:2006
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负责人:Matthew Hahn
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依托单位:
Postdoctoral Research Fellowship in Interdisciplinary Informatics for FY 2003
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批准号:0305994
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项目类别:Fellowship Award
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资助金额:$10.0万
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财政年份:2003
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负责人:Matthew Hahn
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依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data
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批准号:60601030
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项目类别:青年科学基金项目
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资助金额:17.0万元
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批准年份:2006
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负责人:Axel Mosig
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依托单位: