Computational Approaches to Virus Phylogenetics

病毒系统发育学的计算方法

• 批准号: 9974525
• 负责人: David Mindell
• 金额: $ 42.94万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-15 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9974525&HistoricalAwards=false
• 关键词: Computational; Approaches; Virus; Phylogenetics

DBI 9974525, Goldstein, Richard, University of Michigan. Computational Approaches to Virus phylogeneticsProject SummaryViruses are important agents affecting the health and genomic evolution of almost all life forms, in addition to providing experimental models in many areas of basic and applied research. An important aspect of understanding the origin, transmission, and evolution of these viruses is dependent on our ability to understand their phylogenetic history. Unfortunately, our knowledge of this history has been hampered by a lack of understanding of how to model viral genomic evolution. While much work has been done by analyzing the evolution of viral DNA sequences, there are many advantages in modeling evolutionary change of the expressed proteins at the amino acid level. Generating accurate models for amino acid substitutions has, however, proven problematic. One of the challenges in developing an accurate model is dealing with the problem of "site heterogeneity", the qualitative and quantitative variation in substitution rates at different locations in a protein and in different proteins. In recent work, the PIs have developed a theoretical framework for modeling the substitution process in a way that takes into account the context-dependence of selective pressure while actually reducing the number of adjustable parameters to be determined. In this project the PIs will continue to develop these methods, and apply these methods to address basic questions in viral evolution.Specific projects will include:Continued development and refinement of models of the substitution process in protein evolution.Development of more efficient optimization methods for adapting these models to specific proteins and protein types.Validation of these models through analysis of simulated data as well as analysis of proteins from organisms with a known phylogenetic history.Applying these methods to a set of questions including the phylogeny of HIV1 subtypes and lentivirus genera.Interpretation of the results to better understand the process of molecular evolution in viruses.

密歇根大学理查·戈尔茨坦，DBI 9974525。病毒系统发育的计算方法项目概述病毒是影响几乎所有生命形式的健康和基因组进化的重要因素，此外还在许多基础和应用研究领域提供实验模型。了解这些病毒的起源、传播和进化的一个重要方面取决于我们了解它们的系统发育历史的能力。不幸的是，由于缺乏对如何模拟病毒基因组进化的理解，我们对这段历史的了解一直受到阻碍。虽然通过分析病毒DNA序列的进化已经做了很多工作，但在氨基酸水平上模拟表达蛋白质的进化变化具有许多优势。然而，事实证明，建立准确的氨基酸替代模型是有问题的。开发准确模型的挑战之一是处理“位置异质性”问题，即在蛋白质和不同蛋白质中不同位置的替换率的质和量的变化。在最近的工作中，PI开发了一个理论框架来模拟替代过程，这种方法考虑了选择压力的上下文依赖性，同时实际上减少了待确定的可调参数的数量。在这个项目中，PIs将继续开发这些方法，并将这些方法应用于解决病毒进化中的基本问题。具体项目将包括：继续开发和完善蛋白质进化中替代过程的模型，开发更有效的优化方法，使这些模型适用于特定的蛋白质和蛋白质类型。通过分析模拟数据和分析具有已知系统发育历史的生物的蛋白质来验证这些模型。将这些方法应用于一系列问题，包括HIV1亚型和慢病毒属的系统发育。解释结果，以更好地理解病毒的分子进化过程。