Our ability to sequence DNA has rapidly outpaced our understanding of how best to utilize such massive amounts of data for phylogenetics. My lab's research aims to help close this gap by developing methods both for inferring phylogenies and using the information they contain to answer interesting biological questions. I will discuss two of our ongoing methodological projects. The first involves a new approach to identify those parts of the genome that provide the most reliable phylogenetic estimates. The second uses network mathematics to summarize the phylogenetic information in collections of trees. This approach can potentially be used to detect "rogue" taxa, species with hybrid origins, horizontally transferred genes, systematic error, as well as to provide better visual summaries of phylogenetic information and improve checks of MCMC convergence. I will also touch on some empirical work comparing the amount and quality of phylogenetic information provided by different approaches to genome-wide sequencing, focusing on the phylogenetic placement of turtles.