Collaborative Research: ABI Innovation: Quantifying and Exploiting the Structure of Phylogenetic Tree Space Through Network Analyses

该项目将开发一个丰富而灵活的数学框架，用于量化包含在基因组序列大数据集中的系统发育信号（即生物体之间的系谱关系信息）。为了量化这个信号，不同系统发育树之间的关系，或者这些树中的分支，将被概念化为网络。这些网络的结构提供了关于系统发育不确定性和冲突的程度和原因的生物学上有意义的信息。新开发的框架将在可作为独立应用程序和web服务使用的公开软件中实现。此外，开发软件的核心功能将与其他正在进行的nsf资助的重建和探索生命之树（iPlant和开放生命之树）的努力紧密结合。这项工作将借鉴进化生物学、计算机科学和应用数学方面的专业知识。研究活动将涉及研究生和本科生的研究人员和软件开发人员的直接贡献。本科生将通过师徒关系从研究生那里学习编程。科学传播学本科学生将开发一个网站，说明系统发育原理和应用系统发育研究，突出所开发的方法提供的新见解。此外，还将举行几次面对面和远程培训讲习班，向研究人员介绍和熟悉新开发的工具。路易斯安那州立大学将举办一场针对本科生的计算生物学系列研讨会。作为该项目的一部分开发的方法将提高我们理解系统发育信息的能力，这对于保护，法医学，农业和流行病学的各种应用是不可或缺的。项目进展的最新情况和已开发工具的链接将在http://www.phyleauxgenetics.org/上提供。

This project will develop a rich and flexible mathematical framework for quantifying the phylogenetic signal (i.e., the information about genealogical relationships among organisms) contained within big data sets of genome sequences. To quantify this signal, the relationships among different phylogenetic trees, or the branches in those trees, will be conceptualized as networks. The structure of these networks provides biologically meaningful information about the degree and causes of phylogenetic uncertainty and conflict. The newly developed framework will be implemented in publicly available software useable as a standalone application and as a webservice. In addition, the core functionality of the developed software will be closely integrated with other ongoing NSF-funded efforts to reconstruct and explore the Tree of Life (iPlant and the Open Tree of Life).This work will draw from expertise in evolutionary biology, computer science, and applied mathematics. Research activities will involve the direct contributions of both graduate and undergraduate researchers and software developers. Undergraduates will learn to code from graduate students in mentor-apprentice relationships. An undergraduate science communications student will develop a website illustrating phylogenetic principles and applied phylogenetic research, highlighting novel insights provided by the methods developed. Additionally, several in-person and remote training workshops will be held to introduce and familiarize researchers with newly developed tools. An ongoing computational biology seminar series targeted towards undergraduates will be held at Louisiana State University. The methods developed as part of this project will improve our ability to understand phylogenetic information, which is integral to a variety of applications in conservation, forensics, agriculture, and epidemiology. Updates on project progress and links to developed tools will be available at http://www.phyleauxgenetics.org/.