Statistics and Algorithms in Evolution

凝聚理论是数学进化理论的一个分支，始于80年代初的S，与以往的方法相比，它提供了一种计算高效的遗传样本统计分析方法，例如模拟Wright-Fisher模型。由于HapMap计划正在绘制人类的单倍型图谱，它对于理解全基因组关联研究，从而确定导致人类疾病的单核苷酸多态(SNPs)具有重要意义。结合理论最近的活跃研究领域包括人类重组率的测定，特别是所谓的重组热点的预测。重组热点的位置是解释连锁不平衡的关键，连锁不平衡影响了全基因组关联研究的数据解释。 我们正在研究聚结理论，开发一个可扩展的计算机模拟聚结的框架。特瓦里博士正在研究教科书中的联合理论的基本数学，并吸收相关文献。他目前正在编写一套精心记录的Java程序，目标是对合并过程和相关过程(如重组)进行面向对象的建模。

Coalescent theory is a branch of mathematical evolutionary theory that began as recently as the early 80's. Its methods provide a computationally efficient statistical analysis of genetic samples compared to previous methods, e.g., simulation of the Wright-Fisher model. Because of the HapMap Project, which is elaborating a haplotype map of human beings, it has implications for the understanding of genome-wide associations studies, and thereby the determination of single nucleotide polymorphisms (SNPs) that contribute to human disease. Active areas of recent research in coalescent theory include the determination of human recombination rates, and in particular the prediction of so-called recombination hot-spots. The location of recombination hot-spots is critical to interpreting linkage disequilibrium, which influences the interpretation of data from genome-wide association studies. We are studying coalescent theory and developing an extensible framework for simulating coalescence by computer. Dr. Tewari is studying the basic mathematics of coalescent theory from textbooks and absorbing the relevant literature. He is presently writing a suite of carefully documented Java programs, with the aim of object-oriented modeling of the coalescent process, and related processes like recombination.