Methods and software for the analysis and classification of evolutionary and biomedical data

用于进化和生物医学数据分析和分类的方法和软件

• 批准号: 249644-2011
• 负责人: Makarenkov, Vladimir
• 金额: $ 3.06万
• 依托单位: Université du Québec à Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=570673
• 关键词: Methods; software; analysis; classification; evolutionary

My research proposal involves four major components: 1. A number of important evolutionary mechanisms can be only explained by the phenomenon of reticulate evolution which allows for additional evolutionary relationships among species compared to the classical model of a phylogenetic tree. First, I propose to develop two algorithms, based on the distance and probabilistic approaches respectively, for the prediction and validation of partial horizontal gene transfer events and the resulting intragenic recombination. The developed algorithms will be applied on a genome scale to estimate the proportion of mosaic genes in genomes of prokaryotes and phages, and used to assess the impact of HGT and intragenic recombination on the resistance of bacteria to antibiotics. 2. Development of two methods and associated software for the analysis and representation of reticulate evolution by hybridization networks. First, I will design a method for computing the smallest number of hybridization events required to explain conflicting gene trees; and, second, I will develop a method for determining whether the relationships among the species at hand should be represented by a phylogenetic tree or by a hybridization network. 3. Investigate the problem of multiple sequence realignment and of joint inference of a phylogeny and a multiple sequence alignment (MSA). The methods developed under this research component will be able to realign long genomic regions and carry out topological rearrangements of the phylogeny in order to optimize the agreement between the final tree topology and the given MSA. 4. Design and implement methods for the analysis and correction of high-throughput screening (HTS) data. I plan to develop two techniques for improving the hit selection procedure in experimental HTS. The proposed methods and related software will allow researchers to minimize the impact of systematic error affecting the selection of potential drug candidates.

我的研究计划包括四个主要部分： 1.许多重要的进化机制只能用网状进化现象来解释，与系统发育树的经典模型相比，网状进化现象允许物种之间存在额外的进化关系。首先，我建议开发两种算法，分别基于距离和概率的方法，预测和验证部分水平基因转移事件和由此产生的基因内重组。所开发的算法将在基因组规模上应用，以估计原核生物和大肠杆菌基因组中嵌合基因的比例，并用于评估HGT和基因内重组对细菌抗生素耐药性的影响。 2.开发两种方法和相关软件，用于通过杂交网络分析和表示网状进化。首先，我将设计一种方法，用于计算解释冲突基因树所需的最小杂交事件数;其次，我将开发一种方法，用于确定手头的物种之间的关系是否应该由系统发育树或杂交网络来表示。 3.研究多序列重新排列问题以及同源性和多序列排列（MSA）的联合推断问题。在该研究组成部分下开发的方法将能够重新排列长基因组区域，并进行遗传学的拓扑重排，以优化最终树拓扑结构与给定MSA之间的一致性。 4.设计和实施高通量筛选（HTS）数据的分析和校正方法。我计划开发两种技术，以改善实验HTS中的命中选择程序。所提出的方法和相关软件将使研究人员能够最大限度地减少系统误差对潜在候选药物选择的影响。