This project will involve learning to utilize bioinformatic tools to do data analyses on a number of molecular datasets. The datasets come from published studies of different plants groups at the genus-, family-, and order-level. In addition, a new dataset for the endemic Hawaiian genus Schiedea may be generated this summer and the intern can help generate one of the four datasets that will be used in newer methods that test for deep coalescence. Deep coalescence occurs when the species and gene trees that make up a phylogenetic tree do not agree in their evolutionary histories. Schiedea is a good system in which to test if deep coalescence might improve phylogenetic resolution. Ultimately, the goal for these datasets is to construct new phylogenetic hypotheses and to determine whether newer bioinformatic methods can help resolve problematic areas in the trees. This internship will be conducted remotely through online mentoring sessions.