New algorithms for the classification and visualisation of evolutionary and biomedical data

我的研究建议包括四个主要部分：1.物种进化长期以来只用系统发育树来模拟。在这样的树中，每个物种都有唯一的最近祖先，而其他物种间的关系，如水平基因转移或杂交引起的关系，不能被代表出来。首先，我建议开发两种方法，分别基于距离和概率方法，用于预测和可视化可能的水平基因转移事件。考虑到一些重要的进化约束的完全和部分基因转移模型将被考虑。2.第二，我打算开发一种用混合网络分析和表示网状进化的方法。我将设计一个算法和相应的软件来计算解释冲突基因树所需的最小杂交事件数量，并开发一个算法来确定是否可以通过同时发生的网状事件来实现任意有根网络。3.第三，我建议继续从含有缺失碱基的序列数据中进行系统发育推断问题的研究。一种新的有效方法将被设计并在模拟中测试，该方法允许人们在计算未知核苷酸之间的进化距离之前估计它们。4.我的第四个目标是设计和实现研究和校正高通量筛选(HTS)数据的方法。高通量筛选是一种有效的药物发现技术。我计划在HTS实验期间开发两种方法来调整命中选择程序。拟议的技术将使研究人员能够将影响潜在药物靶标选择的系统误差的影响降至最低。

My research proposal includes four major parts: 1. Species evolution has long been modeled using only phylogenetic trees. In such a tree, each species has a unique most recent ancestor, whereas other interspecies relationships, such as those caused by horizontal gene transfers or hybridization, cannot be represented. First, I propose to develop two methods, based on the distance and probabilistic approaches respectively, for the prediction and visualization of possible horizontal gene transfer events. The complete and partial gene transfer models allowing for a number of important evolutionary constraints will be considered. 2. Second, I intend to develop a method for the analysis and representation of reticulate evolution by hybrid networks. I will design an algorithm and corresponding software for computing the smallest number of hybridization events required to explain conflicting gene trees and develop an algorithm to determine whether an arbitrary rooted network can be realized by contemporaneous reticulation events. 3. Third, I propose to continue the investigation of the problem of phylogenetic inference from sequence data containing missing bases. A new effective approach allowing one to estimate unknown nucleotides prior to computing the evolutionary distances between them will be designed and tested in simulations. 4. My fourth objective consists of designing and implementing methods for studying and correcting high-throughput screening (HTS) data. High-throughput screening is an effective technology for drug discovery. I plan to develop two methods for adjusting the hit selection procedure during HTS experiments. The proposed techniques will allow researchers to minimize the impact of systematic error affecting the selection of potential drug targets.