Scalable Algorithms for Reconstruction of Plant Phylogenies in Conjunction with the NSF (National Science Foundation) iPlant Collaborative

进化关系的知识是生物学的基础，在植物科学中产生新的见解，从比较基因组学，分子进化，到植物发育，适应研究，物种形成，群落组装和生态系统功能。尽管我们对绿色植物系统发育的了解已经大大增加，但为50万种绿色植物组装一个全面的生命树的任务仍然令人望而生畏。在分析和综合数据以组装树时，我们面临的主要障碍。这提出了一个巨大的挑战，它需要扩展系统发育生物学和计算机科学之间正在发展的交叉点。在美国国家科学基金会的iPlant合作项目中，我们建议将植物和计算机科学家聚集在一起，专注于收集绿色植物系统发育的所有知识，并推断出比现有树木大100倍的全面系统发育，并将植物生命之树与其他植物学科学相结合。TU m<e:1> nchen与植物生命树的合作将集中在开发新的算法和并行化策略上，以推断由至少50万个分类群组成的单基因植物树。可扩展的树木重建方法是拟议的NSF合作成功的关键组成部分。

Knowledge of evolutionary relationships is fundamental to biology, yielding new insights across the plant sciences, from comparative genomics, molecular evolution, to plant development, the study of adaptation, speciation, community assembly, and ecosystem functioning. Although our knowledge of the phylogeny of green plants has expanded dramatically, the task of assembling a comprehensive tree of life for the half million species of green plants remains daunting. Major barriers confront us in analyzing and synthesizing the data for assembling the tree. This presents a Grand Challenge, which requires expansion of a developing intersection between phylogenetic biology and the computer sciences.Within the NSF iPlant collaborative project we propose to bring plant and computer scientists together to focus on the grand challenge of assembling all knowledge of the phylogeny of green plants and infer a comprehensive phylogeny 100 times larger than existing trees and to integrate the plant tree of life with the rest of botanical sciences. The work at TU München in conjunction with the plant tree of life will focus on developing new algorithms and parallelization strategies to infer single-gene plant trees consisting of at least 500,000 taxa. Scalable methods for tree reconstruction represent a key component for the success of the proposed NSF collaborative.