Extending Bayesian Phylogenetic Analysis

扩展贝叶斯系统发育分析

• 批准号: 8209075
• 负责人: John P. HUELSENBECK
• 金额: $ 29.03万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2013-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8209075
• 关键词: Accounting; Algorithms; Amino Acids; Applications Grants; Bacterial Genome; Bayesian Analysis; Beryllium; Biology; Complex; Computational Biology; Computer software; DNA Sequence; DNA Sequence Analysis; Data; Elements; Evolution; Free Energy; Gene Expression; Genes; Genetic Drift; Genome; Genomics; Goals; Grouping; Horizontal Gene Transfer; Learning; Markov Chains; Methodology; Methods; Mind; Minority; Modeling; Monte Carlo Method; NCI Scholars Program; Natural Selections; Organism; Paper; Pattern; Phylogenetic Analysis; Phylogeny; Process; Proteins; RNA; Recording of previous events; Recruitment Activity; Regulation; Relative (related person); Research; Research Project Grants; Scientist; Shapes; Stretching; Structure; Students; Training Support; Trees; Work; comparative; comparative genomics; computer program; design; gene function; genome sequencing; improved; innovation; interest; next generation; programs; protein structure prediction; public health relevance

DESCRIPTION (provided by applicant): For genomic analyses of bacterial genomes, horizontal gene transfer is a complicating factor, causing different genes to have discordant histories. I plan to develop methods for estimating bacterial species phylogeny in the face of this horizontal gene transfer. I will also develop methods that allow the biologist to uncover patterns in the data, by grouping together genes that have similar realized values of evolutionary parameters. Finally, I will develop more realistic models of protein evolution that take advantage of the most cutting-edge work for the ab initio prediction of protein structure. Using the same statistical framework, I will attempt to predict RNA secondary structure by combining information on the Gibb's free energy with comparative sequence information. The methods developed in the course of this research will be implemented in the next generation of the MrBayes software. 1 PUBLIC HEALTH RELEVANCE: The comparison of DNA sequences from different organisms allows scientists to learn about the processes that shape genomes. For example, by comparing the DNA sequences of deferent genes, we can learn about how natural selection has acted. This proposal develops improved methods for the analysis of DNA sequences. 1

描述(申请人提供)：对于细菌基因组的基因组分析，水平基因转移是一个复杂的因素，导致不同的基因具有不一致的历史。面对这种水平的基因转移，我计划开发评估细菌物种系统发育的方法。我还将开发一些方法，允许生物学家通过将具有相似进化参数实现值的基因组合在一起，来发现数据中的模式。最后，我将开发更现实的蛋白质进化模型，利用最尖端的工作对蛋白质结构进行从头计算预测。使用相同的统计框架，我将尝试通过结合关于Gibb自由能的信息和比较序列信息来预测RNA二级结构。 在本研究过程中开发的方法将在下一代MR Bayes软件中实现。1 与公共卫生相关：通过比较不同生物体的DNA序列，科学家可以了解形成基因组的过程。例如，通过比较不同基因的DNA序列，我们可以了解自然选择是如何起作用的。这项提议开发了分析DNA序列的改进方法。1