Mathematical Challenges in Phylogenetic Landscapes

系统发育景观中的数学挑战

• 批准号: 0920920
• 负责人: Katherine St. John
• 金额: $ 22.12万
• 依托单位: Research Foundation Of The City University Of New York (Lehman)
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0920920&HistoricalAwards=false
• 关键词: Mathematical; Challenges; Phylogenetic; Landscapes

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The goal of this project is to develop innovative mathematics tocompare, optimize and visualize phylogenetic, or evolutionary,trees. We will analyze, via a combination of theoreticaladvances and computational experimentation, the metric space oftrees. Our efforts will focus on better understanding of andimproving algorithms for calculating biologically relevant treemetrics. We will focus on the interaction between these metricsand the canonical, but NP-hard, optimization criteria favored bybiologists. Computationally expensive searches are currentlyused to estimate the optimum and can survey only a tiny fractionof treespace. Deeper understanding of treespace will improvesearches and sampling methods by suggesting better startingpoints, identifying clustering of local optima and suggestinglocations of global optima.Phylogenies, or evolutionary histories, play a central role inmodern biology, illustrating the interrelationships betweenspecies, and also aiding the prediction of structural,physiological, and biochemical properties that can lead to thediscovery of new drugs and vaccines. The reconstruction of theunderlying evolutionary history from a set of morphologicalcharacters or biomolecular sequences is difficult since theoptimality criteria favored by biologists are hard to compute,and the space of possible answers is huge. Due to this, cleversearching techniques and heuristics are used to estimate theoptimal tree. To improve these important, and computationallyintensive, methods, we propose to step back and rigorouslyexamine the underlying space of trees, along with differentoptimality criteria (often called the ?landscape? of trees), andprovide a detailed understanding of the space of trees to improvephylogenetic tree reconstruction.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。该项目的目标是发展创新的数学来比较、优化和可视化系统发育或进化树。我们将通过结合理论进展和计算实验来分析树的度量空间。我们的努力将集中在更好地理解和改进计算生物学相关树形学的算法。我们将重点讨论这些指标与生物学家青睐的典型的NP-hard优化标准之间的相互作用。计算上昂贵的搜索目前用于估计最优，并且只能调查一小部分树空间。对树空间的深入理解将通过提出更好的起点、识别局部最优的聚类和建议全局最优的位置来改进研究和采样方法。系统发生或进化历史在现代生物学中起着核心作用，它说明了物种之间的相互关系，也有助于预测结构、生理和生化特性，这些特性可以导致新药和疫苗的发现。从一组形态特征或生物分子序列重建潜在的进化史是困难的，因为生物学家青睐的最优性标准很难计算，而且可能的答案空间是巨大的。由于这一点，聪明的搜索技术和启发式被用来估计最优树。为了改进这些重要且计算密集的方法，我们建议退后一步，严格检查树木的底层空间，以及不同的最优性标准（通常称为“景观”）。，并提供对树木空间的详细了解，以改善系统发育树的重建。