Frederick (a.k.a. Erick) A. Matsen Miller institute fellow UC Berkeley Dept. Statistics 367 Evans Hall #429 Berkeley, CA 94720-3860 USA ph: +1 510 642 2450 fax: +1 510 642 7892 CV

Overview of research

I like to prove theorems and develop algorithms to answer questions in evolutionary biology.

• Foundations of phylogenetics:     Although phylogenetic methods are known to produce correct results when data conforms to simple models of evolution, it is crucially important to understand how they perform when presented with the sorts of model violations one sees in real data. My research in this area has elucidated the underlying geometry to show that indeed, strange things can happen. My collaborators for this work have been Elchanan Mossel and Mike Steel.
• Phylogenetic algorithm development and applications:     Recently it has been very exciting for me to apply my knowledge of phylogenetics to algorithm development and applications. Over the last year, I have initiated collaborations with the Mullins HIV lab and the Armbrust oceanography lab, both top-notch research labs at the University of Washington. For these collaborations, I have developed phylogenetic algorithms to help answer important research questions in their area. In addition, working on applied problems has helped me find new directions for fundamental phylogenetics research. One of these new directions has resulted in a novel neighbor-joining type algorithm for correlated sets of trees, as one might see in the presence of recombination.
• Probabilistic evolutionary models:     I have enjoyed working on models from two perspectives: first, how can we use phylogenetics to test evolutionary models? I have written papers on this question from algebraic, geometric, and recursive perspectives, as well as developing the first method which uses relative timing information. Second, I am interested in the models themselves, and have contributed to coalescent theory and answered some long-standing questions concerning biparental ancestry. My collaborators for this work have been Daniel Ford, Steve Evans, Tanja Stadler, and John Wakeley.

Publications

[PDF] F. A. Matsen. constNJ: an algorithm to reconstruct sets of phylogenetic trees satisfying pairwise topological constraints. Submitted to J. Comput. Biol.

[PDF] F.A. Matsen and S.N. Evans. Ubiquity of synonymity: almost all large binary trees are not uniquely identified by their spectra or their immanantal polynomials. Manuscript under preparation. arXiv:q-bio/0512010.

[PDF] D. Ford, T. Gernhard, and F. A. Matsen. A method for investigating relative timing information on phylogenetic trees. Accepted to Sys. Biol.

[PDF] F. A. Matsen. Fourier transform inequalities for phylogenetic trees. IEEE TCCB. In press.

[PDF] F. A. Matsen and S. N. Evans. To what extent does genealogical ancestry imply genetic ancestry? Theor. Pop. Biol. In press.

[PDF] F.A. Matsen, E. Mossel, and M. Steel. Mixed-up trees: the structure of phylogenetic mixtures. Bull. Math. Biol., 70(4):1115–1139, 2008.

[PDF] F.A. Matsen and M. Steel. Phylogenetic mixtures on a single tree can mimic a tree of another topology. Sys. Biol., 56:767–775, Oct 2007.

[PDF] M. Steel and F. A. Matsen. The Bayesian star paradox persists for long finite sequences. Mol. Biol. Evol., 24(4):1075–1079, April 2007.

[PDF] F.A. Matsen. Optimization over a class of tree shape statistics. IEEE TCBB, 4:506–512, 2007.

[PDF] F.A. Matsen. A geometric approach to tree shape statistics. Sys. Biol., 55(4):652–661, 2006.

[PDF] F.A. Matsen and J. Wakeley. Convergence to the island-model coalescent process in populations with restricted migration. Genetics, 172(1):701–708, January 2006.

[PDF] F.A. Matsen and M.A. Nowak. Win-stay, lose-shift in language learning from peers. PNAS, 101(52):18053–18057, December 2004. Commentary by K. Sigmund.

Software

constNJ     software to reconstruct sets of phylogenetic trees satisfying pairwise topological constraints

simmons     My software to compute tree shape statistics.

alga, etc.     The source code for the genetic algorithm and related software described in Optimization…

Last modified November 11, 2009.

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