FRIENDLY GRANT FOR INCOMING FACULTY MEMBER
FRIENDLY GRANT FOR INCOMING FACULTY MEMBER
批准号:
8364244
负责人:
DANNIE DURAND
金额:
$0.11万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-15 至 2013-07-31
关键词:
AlgorithmsAutomationBiomedical ResearchData SetEventEvolutionFacultyFundingGene DuplicationGene FamilyGenomeGenomicsGrantHandHigh Performance ComputingLiteratureMethodsMolecular EvolutionMutationNational Center for Research ResourcesPrincipal InvestigatorRecording of previous eventsResearchResearch InfrastructureResourcesSourceStructureTreesUnited States National Institutes of Healthaging genecostdesigngene functionmember
中文摘要
这个子项目是许多利用资源的研究子项目之一
由NIH/NCRR资助的中心拨款提供。子项目的主要支持
而子项目的主要调查员可能是由其他来源提供的,
包括其它NIH来源。 列出的子项目总成本可能
代表子项目使用的中心基础设施的估计数量,
而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。
基因复制是基因家族和基因组结构进化的重要机制。确定基因复制的年龄对于理解现代基因组中进化事件和基因功能之间的关系非常重要。一般来说,基因复制日期不能直接从序列中确定,因为突变率不是恒定的。然而,我们可以通过使用进化树校准物种形成事件的重复来估计基因重复发生的时间。许多关于基因复制年代测定的研究出现在分子进化文献中。这些分析是手工进行的。数据集正在大幅增长,以至于它们现在已经达到了传统方法可以分析的极限,即使是现有的数据集也承认替代假设,如果没有自动化,这些假设将过于繁琐。我的研究涉及算法的设计和实现,以自动分析基因复制事件的历史,为大规模基因组分析提供一个构建模块。
英文摘要
This subproject is one of many research subprojects utilizing the resources
provided by a Center grant funded by NIH/NCRR. Primary support for the subproject
and the subproject's principal investigator may have been provided by other sources,
including other NIH sources. The Total Cost listed for the subproject likely
represents the estimated amount of Center infrastructure utilized by the subproject,
not direct funding provided by the NCRR grant to the subproject or subproject staff.
Gene duplication is a crucial mechanism in the evolution of gene families and genomic structure. Determining the age of gene duplications is important to understanding the relationship between evolutionary events and gene function i modern genomes. Gene duplication dates cannot, in general, be determined directly from sequence because mutation rates are not constant. We can, however, estimate when gene duplications took place by calibrating duplication with respect to speciation events using evolutionary trees. Many studies of gene duplication dating have appeared in the molecular evolution literature. These analyses have been performed by hand. Data sets are growing substantially, so that they are now at the limit of what can be analyzed by traditional methods, and even existing data sets admit alternative hypotheses which would be too tedious to consider without automation. My research involve the design and implementation of algorithms to analyze the history of gene duplication events automatically, providing a building block for large-scale genomic analysis.
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