Area of Interest

Every living thing on Earth shares at least two qualities. First, they contain genomes that influence their interactions with the rest of the world. Second, they are the products of long evolutionary histories that have molded their genomes in very particular ways. Our work involves both using genomic data to reconstruct patterns of relatedness (phylogenies) between species, populations, individuals, and genes, as well as understanding what evolutionary forces (e.g., selection, drift, etc.) have acted on different branches of the tree of life to shape genomes. We work across a wide breadth of organisms and time scales. Some recent empirical work has involved:  
- Inferring HIV transmission dynamics
- Studying changes in a hybrid zone of chorus frogs in Louisiana and Mississippi over 40 years
- Describing an anciently diverging lineage of living ants
Much of our work also involves developing statistical and computational tools to analyze genomic data, including:
- Creating visual and analytical tools for exploring large sets of phylogenetic trees
- New approaches for quantifying phylogenetic information
- Identifying sets of genes that provide reliable phylogenetic signal
- Developing new models of sequence evolution for ultraconserved elements (UCEs)
If you're interested in joining the lab, please email. Computational experience is helpful, but not required.

Awards & Honors

Non-tenured Faculty Research Award, 2017, LSU College of Science

Ernst Mayr Award, 2010, Society of Systematic Biologists


Selected Publications

Publication tracking:  Researcher ID , Google Scholar

Brown, J.M. and R.C. Thomson. 2018. Evaluating model performance in evolutionary biology. Annual Review of Ecology, Evolution, and Systematics. In Press.

Höhna, S., L.M. CoghillG.G. Mount, R.C. Thomson, and J.M. Brown. 2018. P3: Phylogenetic Posterior Prediction in RevBayes. Molecular Biology and Evolution. 35:1028-1034.

Barley, A.J., J.M. Brown, and R.C. Thomson. 2017. Impact of model violations on the inference of species boundaries under the multispecies coalescent. Systematic Biology. 67:269-284.

Brown, J.M. and R.C. Thomson. 2017. Bayes factors unmask highly variable information content, bias, and extreme influence in phylogenomic analyses. Systematic Biology. 66:517-530.

Huang, W., G. Zhou, M. Marchand, J. AshD. Morris, P. Van Dooren, J.M. Brown, K.A. Gallivan, and J.C. Wilgenbusch. 2016. TreeScaper: visualizing and extracting phylogenetic signal from sets of trees. Molecular Biology and Evolution. 33:3314-3316.

Doyle, V.P.R.E. Young*, G.J.P. Naylor, and J.M. Brown. 2015. Can we identify genes with increased phylogenetic reliability? Systematic Biology. 64:824-837.

Brown, J.M. 2014. Detection of implausible phylogenetic inferences using posterior predictive assessment of model fit. Systematic Biology. 63(3): 334-348.


* Undergraduates