讲座报告:莱斯大学计算机系主任Luay Nakhleh教授学术报告三:Elucidating Intratumor Heterogeneity from Single-cell DNA Sequencing Data

时间 2019年09月19日 14:00 - 15:30
地点 一校区新技术楼618室
网址

  应计算机科学与技术学院院长王亚东教授邀请,在国际项目管理中心的大力支持下,美国莱斯大学计算机系主任Luay Nakhleh教授将于2019年9月15日至9月22日对我校计算机学院进行学术访问。访问期间将开展三次学术报告。欢迎感兴趣的师生参加。

报告三

  报告主题:Elucidating Intratumor Heterogeneity from Single-cell DNA Sequencing Data

  报告时间:2019年9月19日 14:00-15:30

  报告地点:一校区新技术楼618室

  报告摘要:Intra-tumor heterogeneity, as caused by a combination of mutation and selection, poses significant challenges to the diagnosis and clinical therapy of cancer. Resolving this heterogeneity to identify the tumor cell populations (clones) and delineate their evolutionary history is of critical importance in improving cancer diagnosis and therapy. This heterogeneity can be readily elucidated and understood through the reconstruction of the clonal genotypes and evolutionary history of the tumor cells. These tasks are challenging since genomic data is most often collected from one snapshot during the evolution of the tumor's constituent cells. Consequently, using computational methods that infer the tumor phylogeny and tumor subpopulations from sequence data is the approach of choice. Recently emerged single-cell DNA sequencing (SCS) technologies promise to resolve intra-tumor heterogeneity to a single-cell level. However, inherent technical errors in SCS datasets, including false-positive (FP) errors, false-negatives (FN) due to allelic dropout, cell doublets and coverage non-uniformity significantly complicate these tasks.

    In this talk, I will first describe a maximum likelihood method for inferring tumor trees from imperfect SCS genotype data with potentially missing entries, under a finite-sites model of evolution. I will then describe a non-parametric Bayesian method that simultaneously reconstructs the clonal populations as clusters of single cells, mutations associated with each clone, and the genealogical relationships between the clonal populations. I will demonstrate the performance of the methods on both synthetic and real data sets.

 

  主讲人:Luay Nakhleh教授,博士毕业于德克萨斯大学奥斯汀分校计算机科学专业。研究领域为生物信息学和计算生物学。尤其是针对生物进化和基因学领域的研究。曾出版100余篇学术文章,发表100余场学术报告。获得过众多奖项,如德克萨斯杰出教学奖(德克萨斯州大学中最有声望的奖项之一);DOE事业奖等奖项。

  莱斯大学(Rice University),简称Rice,位于美国得克萨斯州休斯敦市郊。为美国南方最高学府,美国大学协会(AAU)成员,是一所世界著名的顶尖私立研究型大学,“新常春藤”名校之一。

原文:http://today.hit.edu.cn/article/2019/09/10/69967

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