Statistical and Computational Methods for the Study of Gene Families

基因家族研究的统计和计算方法

• 批准号: 0543586
• 负责人: Matthew Hahn
• 金额: $ 36.02万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0543586&HistoricalAwards=false
• 关键词: Statistical; Computational; Methods; Study; Gene

Indiana University is awarded a grant to develop a statistical framework that would allow for inferences regarding gene family evolution among species. In order to take full advantage of the data being produced by various genome sequencing projects, this project aims to extend the statistical and computational tools necessary for biological researchers to study gene families. There are three main goals of this proposal: 1) Development of improved statistical tools. This work will enable more refined estimates of gene duplication and deletion parameters between species, and will provide new ways in which to study gene families within single genomes. The inclusion of methods for detecting and incorporating whole genome duplications will greatly extend statistical inferences. 2) Creation of easy-to-use software. A free software package will be implemented that can be used by researchers studying whole genomes or individual gene families. Statistical tools created in this project will be quickly disseminated to the community via this package. 3) Providing annotated gene families for Drosophila. The sequencing of 12 Drosophila species will be a boon to comparative genomics studies. By working with FlyBase to provide a well-annotated set of gene families from across these species, we will present new ways for biologists to connect this information with functional and comparative genomic data. The products of this research will provide a broad statistical and computational framework for all future studies of gene families. The research will also provide a diverse training environment for undergraduates, graduate students, and postdoctoral researchers in molecular evolution, statistics, and bioinformatics. The participation of under-represented groups and women via multiple scholarship programs will ensure that this specific research priority is achieved. The research will also be used in the development of classes and programs for understanding the relationship between biodiversity and genetic variation, and in graduate education for bioinformatics students.

印第安纳大学获得了一笔拨款，用于开发一个统计框架，该框架将允许对物种之间的基因家族进化进行推断。为了充分利用各种基因组测序项目产生的数据，该项目旨在扩展生物学研究人员研究基因家族所需的统计和计算工具。本提案有三个主要目标：1)发展改进的统计工具。这项工作将使物种之间基因复制和缺失参数的估算更加精确，并将为研究单个基因组中的基因家族提供新的方法。纳入检测和合并全基因组重复的方法将大大扩展统计推断。2)创建易于使用的软件。一个免费软件包将被实现，供研究人员研究整个基因组或单个基因家族使用。在这个项目中创造的统计工具将通过这个包迅速传播给社区。3)为果蝇提供带注释的基因家族。12种果蝇的测序将对比较基因组学研究大有裨益。通过与FlyBase合作，从这些物种中提供一组注释良好的基因家族，我们将为生物学家提供新的方法，将这些信息与功能和比较基因组数据联系起来。这项研究的成果将为所有基因家族的未来研究提供一个广泛的统计和计算框架。该研究还将为分子进化、统计学和生物信息学方面的本科生、研究生和博士后研究人员提供多样化的培训环境。通过多个奖学金项目，弱势群体和女性的参与将确保实现这一特定的研究重点。研究结果也将用于生物多样性与遗传变异关系的课程和计划的发展，以及生物信息学学生的研究生教育。