中央研究院統計科學研究所

學 術 演 講


講 題:Building Evolutionary Trees from SNPs Data: An Ancestral Mixture
    Models Approach

演講人:陳 淑 娟 教 授
    (Department of Mathematics and Statistics, Arizona State University, USA)

時 間:2005年8月1日(星期一)上午10:30-12:00

地 點:中央研究院統計科學研究所二樓交誼廳

※茶會:上午10:10統計所二樓交誼廳


摘 要

  An ancestral mixture model is proposed for clustering discrete multivariate sequences. This model has a natural relationship to the coalescent process of population genetics. The sieve parameter in the model plays an important role of time in the evolutionary tree of the sequences. In this talk, I will show how an ancestral mixture model can be used to build up a hierarchical tree from binary sequence data by sliding the sieve parameter. An example genetic single nucleotide polymorphisms (SNP) data will be used for illustration. Some properties of the ancestral mixture model, such as its nested structure and the relationship to the coalescent process of population genetics, will be presented.
This is a joint work with Professor Bruce Lindsay at Penn State University.