My interests lie at the nexus of biology, statistics, and computer science. My work involves developing and applying Bayesian methods to address novel questions in phylogenetics. I joined the Brown lab as a masters student in fall 2012. My website can be found here.
Research
Detecting host-specific evolution in HIV using phylogenetic methods
Often, rapid adaptation occurs when organisms colonize new habitats, a process traditionally investigated using morphological characters of macroscopic organisms inhabiting island archipelagos. However, studies of macroscopic organisms are limited by slow rates of evolution and the number and kinds of islands available for colonization. Microbial systems lack these shortcomings due to rapid rates of evolution and abundant host populations. For microbial pathogens, host organisms act as islands and transmission events from source to recipient recapitulate the process of island colonization. In phylogenetic trees, the expected result of this process is paraphyly of the source population relative to the recipient.
I am testing whether phylogenetic models that allow for variation between hosts perform better than traditional methods, and whether they detect changes specific to branches that correspond to transmission events.
Improving Bayesian branch length estimates using informed priors
Several studies have shown that for shallow trees with high taxon sampling, Bayesian branch length estimates may differ from maximum likelihood estimates by an order of magnitude. I am working with labmate John Andersen to develop EmpPrior, a program which queries TreeBASE for matching markers and estimates rate parameters for use as priors with focal datasets. Using informed priors greatly improves upon default settings in MrBayes, typically resulting in credible intervals that include the MLE.