Recent News
Computer Science Colloquium will discuss strategies for sustainable AI data centers
March 10, 2025
Dissertation defense: Alyshia Bustos
March 5, 2025
Computer Science undergraduate honored for cybersecurity research
February 20, 2025
Associate Professor Matt Lakin wins PECASE Award
January 31, 2025
News Archives
Phylogenetic Estimation for Complex Evolutionary Processes
March 30, 2006
- Date: Thursday, March 30, 2006
- Time: 11:00 am — 12:15 pm
- Place: Woodward 149
Li-San Wang (UNM Faculty Candidate)
Department of Biology, University of Pennsylvania
Stochastic models of sequence evolution, since their introduction in the 1960s, have inspired the development of numerous computational and statistical methods for phylogeny reconstruction which have been widely successful in reconstructing the evolutionary history of genes and species. However, standard evolutionary models have two essential features, both of which are known to fail for a wide range of real biological data: (1) the domain of mutation is a concatenation of multiple independently distributed sites, each following a simple, identical stochastic process, and (2) the evolutionary history is a branching process (tree).
This talk is an overview of my research on complex evolutionary processes — processes that lack either of the two features of standard models. In both cases, new stochastical models need to be developed. Moreover, the inference of evolutionary histories under these models is much harder – in some cases simply computationally more intense, but in other cases posing significant and new algorithmic challenges.
I will cover two such processes: the process of gene order evolution. and the process of horizontal gene transfer. For each process, I will formulate the estimation problems, identify computational and statistical issues, and present our current results and future research directions.