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`ITR/AP: Collaborative Research: Exploring the Tree of Life

`ITR/AP: Collaborative Research: Exploring the Tree of Life
`ITR/AP:合作研究:探索生命之树
批准号:
0121682
负责人:
Tandy Warnow
金额:
$78.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-09-15 至 2005-08-31

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英文摘要
0121682 and 0121651Amenta, Hillis, and St. JohnDefining and understanding the evolutionary relationships among species is fundamental to contemporary biology and the application of the comparative method in the life sciences. The results of such evolutionary research can be represented by a branching sequence of relatedness among species known as a phylogeny. Because of the geometric resemblance of a phylogeny to the branches of a tree, a phylogeny can be thought of as a tree of life. The proposed collaborative research by biologists and computer scientists at University of Texas-Austin and at CUNY-Lehman College in New York will provide specialized visualization and data mining tools to facilitate creation of a "Tree of Life" for all living organisms on the earth. This includes the development and refinement of algorithms to visualize and analyze multiple complex data sets for large numbers of species. More specifically, this project will: (1) integrate biological data through visualization and clustering techniques developed by computer scientists, and (2) apply these tools to taxa which comprise very large numbers of species with topologically complex and varied tree structures. The interdisciplinary team of biologists and computer scientists will integrate their newly developed software with existing computational tools in systematic biology, and make them freely available to and easily used by the scientific community. The project involves substantive efforts to provide undergraduates and students from under-represented groups with the opportunity to collaborate with scientists throughout the academic year and summer.
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IIBR Informatics: Advancing Bioinformatics Methods using Ensembles of Profile Hidden Markov Models
AitF: Full: Collaborative Research: Graph-theoretic algorithms to improve phylogenomic analyses
ABI Innovation: New methods for multiple sequence alignment with improved accuracy and scalability
III: AF: Medium: Collaborative Research: Scalable and Highly Accurate Methods for Metagenomics
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