Massively Parallel Phylogeny Reconstruction for the Age of DNA Big Data

物种之间有什么关系？这个问题在生命科学中至关重要，原则上可以使用DNA序列数据来解决。这些数据中隐含的是DNA来自的物种的关系模式，称为它们的亲缘关系，通常表示为树。然而，对于非常大的输入，重建系统发生树的算法和软件却落后于最近DNA序列数据的爆炸式增长。本项目的目标是创建并行算法和开放源代码软件，通过适合于非常大数据的启发式搜索来重建大型系统发生树。该项目将使用理论和计算方法。这些将包括自然启发的先进机器学习的使用和表征（例如Strobl和Barker 2016），大规模并行计算机系统的编程和使用，算法和实现的优化，以及跨站点分布式机器学习技术。

How are species related? This question, of fundamental importance across life sciences, can in principle be addressed using DNA sequence data. Implicit in these data is the pattern of relationships of the species the DNA came from, known as their phylogeny, usually represented as a tree. However, algorithms and software to reconstruct phylogenetic trees for very large input are lagging behind the recent explosion in the availability of DNA sequence data.The goal of this project is to create parallel algorithms and open-source software for reconstructing large phylogenies by heuristic searches suited to very large data.The project will use theoretical and computational approaches. These will include use and characterisation of nature-inspired advanced heuristics (e.g. Strobl and Barker 2016), programming and use of massively parallel computer systems, optimisation of algorithms and implementations, and cross-site, distributed machine learning techniques.