Efficient probabilistic inference and Bayesian non-parametrics with applications in phylogenetics and cancer genomics

计算和统计系统发育学的领域涉及对进化关系的建模和推断。近年来，由于测序技术的重要进步，这些领域发展迅速。然而，许多挑战依然存在。一个这样的例子出现在癌症系统发育领域，与癌症肿瘤内进化动力学的表征有关。更具体地说，挑战来自于需要描述单个癌细胞的进化特征，研究人员面对的是获得不同突变集的多个癌细胞亚群的混合物。

The fields of computational and statistical phylogenetics are concerned with the modelling and inference of evolutionary relationships. These fields have grown rapidly in recent years due to important advances in sequencing technologies. Many challenges, however, remain. One such example arises in the area of cancer phylogenetics, and relates to the characterization of evolutionary dynamics within cancer tumours. More specifically, the challenge arises from the need to characterize the evolution of individual cancer cells, where researchers are presented with mixtures of multiple sub-populations of cancer cells that have acquired different sets of mutations.