We are using mathematical models and statistical methods to analyze patterns of genetic variability in natural populations, with the goal of discerning neutral from non-neutral forces of molecular evolution. Current topics include adaptation, epistasis, computer simulations and machine learning. We are also interested in exploring evolutionary links between chromatin structure and DNA sequence. Furthermore, we are using methods of comparative and evolutionary genomics to study the emergence and function of lineage specific genes. Our current focus is on the bilaterian, vertebrate and arthropod nodes of the tree of life.
Selected publications
- Z. Yang, J. Li, T. Wiehe, H. Li (2017) Detecting recent positive selection with a single locus test bi-partitioning the coalescent tree Genetics https://doi.org/10.1534/genetics.117.300401
- L. Ferretti, A. Ledda, T. Wiehe, G. Achaz and S.E. Ramos-Onsins (2017) Decomposing the Site Frequency Spectrum: The Impact of Tree Topology on Neutrality Tests Genetics, 207:229
- K. Howe, P.H. Schiffer, J. Zielinski, T. Wiehe, G.K. Laird, J. Marioni, O. Soylemez, F. Kondrashov, M. Leptin (2015) Structure and evolutionary history of a large family of NLR proteins in the zebrafish Open Biol. 2016:6
- P. Heger, T. Wiehe (2014) New tools in the box: an evolutionary synopsis of chromatin insulators. Trends in Genetics 30:161
- F. Disanto, T. Wiehe (2014) On the sub-permutations of pattern avoiding permutations. Discrete Mathematics 337:127