Reconstructing Phylogenetic Trees

重建系统发育树

• 批准号: 0077851
• 负责人: Thomas Hagedorn
• 金额: $ 6.39万
• 依托单位: The College of New Jersey
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2004-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0077851&HistoricalAwards=false
• 关键词: Reconstructing; Phylogenetic; Trees

Hagedorn0077851 The investigator seeks advances in the reconstruction ofphylogenetic, or evolutionary, trees in biology by improving theutility of the method of phylogenetic invariants, one of severaldifferent methods of tree reconstruction. It would be extremelyuseful to have an accurate, computationally efficient method ofphylogenetic analysis, but no such method is yet known. Themethod of phylogenetic invariants theoretically has theseadvantages. Modern phylogenetic methods analyze the mathematicaland statistical similarities between the nucleotide sequences ofdifferent species. By modeling the evolution of the sequence fora proposed evolutionary tree T as a Markov model, one can obtainpolynomials specifying the frequencies with which certainpatterns should occur in observed sequence data. Thesepolynomials parameterize a high-dimensional real algebraicvariety X. Finding the equations that implicitly define X istheoretically equivalent to knowing how to determine whether T isthe "true" evolutionary tree. These equations have beenpreviously found for special evolutionary models such as theKimura 3-parameter model. The investigator studies theinvariants for the most general Markov model of nucleotidesequences and uses a combination of combinatorics and non-abelianFourier analysis to find a complete set of invariants. He alsoexplores ways to reduce the method's sensitivity to evolutionarynoise and raising its accuracy. Advances on these issues areessential to make implementations of the invariant methodpractical for phylogenetic analysis. The investigator develops better methods to constructbiological trees explaining the evolutionary relationshipsbetween species. Understanding evolutionary relationships is animportant biological question, whose applications range fromaiding the discovery of the origin of life to helping the medicalcommunity research possible vaccines and treatments for pathogenssuch as the H.I.V. virus. It would be extremely useful to havean accurate and computationally efficient method of phylogenetic(or evolutionary) analysis, but no method is currently known topossess both qualities. The project seeks to improve theaccuracy of the tree reconstruction method using phylogeneticinvariants. The method of invariants is a computationallyefficient method, which is known to theoretically give correctanswers. However, in practice, the method is very susceptible tothe presence of noise in the data. The investigator aims tominimize this problem by eliminating several assumptions thatcurrently must be met to use the method of invariants.

Hagedorn0077851 研究者通过改进系统发育不变量方法的实用性来寻求生物学中系统发育或进化树重建的进展，系统发育不变量方法是几种不同的树重建方法之一。 如果有一种精确的、计算效率高的系统发育分析方法，那将是非常有用的，但目前还没有这样的方法。 系统发育不变量法在理论上具有这些优点。 现代系统发育学方法分析不同物种的核苷酸序列之间的遗传相似性和统计相似性。 通过将序列的演化作为一个马尔可夫模型来建模，我们可以得到多项式来指定观察到的序列数据中某些模式应该出现的频率。 这些多项式是高维真实的代数簇X的参数。 找到隐含定义X的方程在理论上等同于知道如何确定T是否是“真正的”进化树。 这些方程以前已经发现了特殊的进化模型，如木村3参数模型。 研究人员研究了最一般的马尔可夫模型的核苷酸序列的不变量，并使用组合数学和非阿贝尔傅立叶分析的组合，以找到一个完整的一套不变量。 他还探索了降低该方法对进化噪声的敏感性并提高其准确性的方法。 在这些问题上的进展是必不可少的，使不变量方法的实现系统发育分析的实用。 研究者开发了更好的方法来构建解释物种之间进化关系的生物树。 理解进化关系是一个重要的生物学问题，其应用范围从帮助发现生命的起源到帮助医学界研究可能的疫苗和治疗病原体（如H.I.V.病毒）。 如果能有一种精确且计算效率高的系统发育（或进化）分析方法将是非常有用的，但目前还没有一种方法同时具备这两种品质。 该项目旨在提高使用遗传不变量的树重建方法的准确性。 不变量法是一种计算效率很高的方法，理论上可以给出正确的变换。 然而，在实践中，该方法是非常容易的tothe存在的噪音的数据。 调查人员的目的是通过消除几个假设，目前必须满足使用的方法不变量最小化这个问题。