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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

基本信息

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

项目摘要

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".

torng， Eric k密歇根州立大学itr：用数字生物体评估系统发育重建算法研究人员仅使用当前存在的生物体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”。许多树重建算法都是已知的，但很难对它们进行适当的测试，因为这些算法很有用——原始树已经消失在历史中。提出的研究利用了一种新的评估方法，该方法基于一种名为Avida的人工进化系统。在阿维达，数字生物（自我复制的计算机程序）的种群在争夺有限的资源时经历了自然选择，并将进化成通常具有全新基因的新物种。这样一个系统的历史可以被监控，因此从最终状态重建它的精度可以被测量。拟议中的活动对社会有几个更广泛的影响。这是密歇根州立大学一个新的跨学科研究和教育中心——生物建模中心的一项核心活动。包括代表性不足的少数民族在内的本科生将参与研究小型的、独立的问题。最后，加强对系统发育重建算法的理解将提高我们解释基因序列的能力，帮助药物设计和帮助重建进化的“生命之树”。