Jack Sullivan

TL;DR: This work develops a novel approach to model selection, which is based on the Bayesian information criterion, but incorporates relative branch-length error as a performance measure in a decision theory (DT) framework.

TL;DR: Issues that render model-based approaches necessary are reviewed, nucleotide-based models that attempt to capture relevant features of evolutionary processes are briefly reviewed, and methods that have been applied to model selection in phylogenetics are reviewed: likelihood-ratio tests, AIC, BIC, and performance- based approaches.

TL;DR: The monophyly of Rodentia has repeatedly been challenged based on several studies of molecular sequence data and it is shown that models that incorporate variation in evolutionary rates across sites fit the data dramatically better than models used in the original analyses.

TL;DR: This work advocates the use of conserved motifs and other secondary structure information for assessing sequencing fidelity, and is similar to previous models but is more specific to mitochondrial DNA, fitting both invertebrate and vertebrate groups.

TL;DR: Analysis of mesic forest ecosystems in the Pacific Northwest of North America using a statistical phylogeography approach shows that genetic data sampled from across an ecosystem can provide insight into the evolution of ecological communities and suggests that the advantages of a statistical phylogenetic and coalescent approach are most pronounced in comparisons across multiple taxa in a particular ecosystem.