Title：Genome Assembly for Third-Generation Sequencing
题目：第三代基因组测序与拼接
Abstract: The recent breakthroughs in assembling long error-prone reads (generated by third-generation sequencing) were based on the overlap-layout-consensus approach and did not utilize the strengths of the alternative de Bruijn graph approach to genome assembly. In this talk, I will show how to generalize the de Bruijn graphs to assemble long error-prone reads and describe our graph approach that results in more accurate genome reconstructions than the existing state-of-the-art algorithms. Moreover, our graph model can also be applied to improving assemblies for second-generation sequencing, bridging the analysis of genome assembly, genome rearrangements and segmental duplications.
摘要： 当前针对第三代基因组测序的主要拼接方法都基于以往的重叠-展开-求同的模型，并没有充分利用针对第二代测序拼接里最常用的De Bruijn图模型。这个报告将展示如何推广de Bruijn图来拼接三代测序数据，并提出基因组拼接的新模型。
我们的图模型也同时可用于改进第二代测序数据的拼接，并将基因组中的基因组拼接，基因组重排和重复片段的分析衔接起来。
Bio: Yu Lin is a Lecturer (Assistant Professor) at the Research School of Computer Science, the Australian National University. Prior to this, he was a postdoctoral scholar, hosted by Prof Pavel Pevzner at the Department of Computer Science and Engineering, University of California, San Diego. He received his PhD in Computer Science under Prof Bernard Moret from École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. His research focuses on computational biology, and he has been working on algorithms for genome assembly, the analysis of genome rearrangements, and phylogenetic reconstruction. He has received two awards from the Swiss National Science Foundation.
个人简历： 林宇博士，讲师（助理教授），目前就职于澳大利亚国立大学计算机学院。他在瑞士联邦理工洛桑分校（EPFL）Bernard Moret教授指导下获得计算机博士学位，之后在加州大学圣地亚哥分校(UCSD) Pavel Pevzner实验室从事博士后研究。他的研究方向是计算生物学， 主要研究兴趣包括基因组拼接，基因组重排和系统发育树构建的模型和算法，并获得过两次瑞士自然科学基金委的项目资助。
