ITR: Evaluating Phylogeny Reconstruction Algorithms with Digital Organisms

ITR：利用数字生物评估系统发育重建算法

• 批准号: 0219229
• 负责人: Eric Torng
• 金额: $ 32.47万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0219229&HistoricalAwards=false
• 关键词: ITR; Evaluating; Phylogeny; Reconstruction; Algorithms

EIA-0219229Torng, Eric KMichigan State UniversityITR: Evaluating Phylogeny Reconstruction Algorithms with Digital OrganismsThe investigators study methods of determining the historic relationshipbetween species using only knowledge of currently existing organisms, a technique called "phylogenetic tree reconstruction". Many tree reconstruction algorithms are known, but it is difficult to properly test them for the veryreason that the algorithms are useful -- the original trees are lost tohistory.The studies proposed make use of a new evaluation methodology based on anartificial evolving system called Avida. In Avida, populations of digitalorganisms (self-replicating computer programs) experience natural selectionas they compete for limited resources, and will evolve into new speciesoften with entirely new genes. The history of such a system can bemonitored, and hence a reconstruction from the final state can have itsaccuracy measured.The proposed activity has several broader impacts on society. It is a coreactivity in the Center for Biological Modeling, a new interdisciplinaryresearch and education center at Michigan State University. Undergraduatestudents including underrepresented minorities will be involved by studyingsmall, self-contained questions. Finally, enhanced understanding ofphylogeny reconstruction algorithms will improve our ability to interpretthesequences of genes, aiding in drug design and helping efforts to reconstructan evolutionary "tree of life".

EIA-0219229 Torng，Eric KMichigan State UniversityITR：用数字生物评估系统发育重建算法研究人员研究了仅使用现有生物的知识来确定物种之间历史关系的方法，这种技术称为“系统发育树重建”。 许多树重建算法是已知的，但它是很难正确地测试他们的veryreason，算法是有用的-原始的树是失去了tohistory.The研究提出利用一种新的评价方法的基础上人工进化系统称为Avida。 在Avida中，数字生物（自我复制的计算机程序）的种群在争夺有限资源时经历了自然选择，并将进化成新的物种，通常具有全新的基因。 这样一个系统的历史可以被监测，因此从最终状态重建的准确性可以被测量。所提出的活动对社会有几个更广泛的影响。 这是生物模型中心的一个共反应性，该中心是密歇根州立大学的一个新的跨学科研究和教育中心。 包括少数民族在内的本科生将参与研究小的，独立的问题。 最后，增强对基因重建算法的理解将提高我们解释基因序列的能力，有助于药物设计和重建进化的“生命之树”。