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".

EIA-0219229TORNG，ERIC KMICHIGAN State Universityitr：使用数字生物体评估系统发育重建算法研究者研究的方法研究方法仅使用当前现有生物体的知识来确定物种之间的历史关系，这是一种称为“系统发育树木结构的技术”。许多树木重建算法都是已知的，但是很难在非常有用的算法中正确测试它们 - 原始树是遗失的史。拟议的研究提出了基于基于Ontraltotal人的新评估方法，该方法基于Onaltertonal evollving System，称为Avida。在阿维达（Avida）中，数字生物的种群（自我复制计算机程序）体验了他们竞争有限资源的自然选择，并将以全新的基因发展成为新的物种。这种系统的历史可能会召唤，因此，最终状态的重建可以衡量其准确性。拟议活动对社会产生了更广泛的影响。它是密歇根州立大学的新跨学科研究中心的生物建模中心的旋转性。研究小组的自我包含的问题将涉及包括代表性不足的少数民族在内的本科生。最后，增强对晶体发育重建算法的理解将提高我们解释基因的解释能力，有助于药物设计并帮助重建进化的“生命之树”的努力。