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ReCombinatorics: Combinatorial Algorithms forStudying the History of Recombination in Populations

机译:重组:组合算法,迫切群体重组史

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The work discussed in this talk falls into the emerging area of Population Genomics. I will first introduce the area and then talk about specific problems and combinatorial algorithms involved in the inference of recombination from population data. A phylogenetic network (or Ancestral Recombination Graph) is a generalization of a tree, allowing structural properties that are not tree-like. With the growth of genomic and population data (coming for example from the HAPMAP project) much of which does not fit ideal tree models, and the increasing appreciation of the genomic role of such phenomena as recombination (crossing-over and gene-conversion), recurrent and back mutation, horizontal gene transfer, and mobile genetic elements, there is greater need to understand the algorithmics and combinatorics of phylogenetic networks. In this talk I will survey a range of our recent algorithmic, mathematical and practical results on phylogenetic networks with recombination and show applications of these results to several issues in Population Genomics. Various parts of this work are joint work with Satish Eddhu, Chuck Langley, Dean Hickerson, Yun S. Song, Yufeng Wu, V. Bansal, V. Bafna and Z. Ding.
机译:本讲台中讨论的工作落入了人口基因组学的新兴地区。我将首先介绍该地区,然后谈论从人口数据中的重组推断中涉及的特定问题和组合算法。系统发育网络(或祖先重组图)是树的泛化,允许非树状的结构性能。随着基因组和人口数据的增长(例如来自HAPMAP项目)的增长,其中大部分都不适合理想的树模型,以及对这种现象的基因组作用的升值越来越大,因为这种现象作为重组(交叉和基因转化),复发和后突变,水平基因转移和移动遗传元素,更需要了解系统发育网络的算法和组合学。在这次谈话中,我将调查一系列我们最近的算法,数学和实际结果对具有重组的系统发育网络,并显示这些结果的应用,以对群体基因组学中的几个问题进行调查。这项工作的各个部分与萨蒂什Eddhu,查克·兰利,院长希克森,云S.宋,吴玉凤,五邦萨尔五Bafna和Z.丁联合工作。

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