We are a small, collaborative group with backgrounds in evolutionary genetics, genomics, computer science, and statistics. Our research develops statistical models and software for population genetic and phylogenetic analysis of DNA and protein sequences. We focus on maximum likelihood and Bayesian methods, creating advanced MCMC algorithms for large genomic datasets, with data analysis both testing our methods and driving new developments.
Collaborations
Learn more about our collaborations with scientists at UCL, other universities, and scientific bodies.
Our principal funders
Selected publications
Kornai D, Jiao X, Ji, Jiayi, Flouri T, Yang Z. 2024. Hierarchical heuristic species delimitation under the multispecies coalescent model with migration. Systematic Biology 73: 1015-1037. DOI: 10.1093/sysbio/syae050.
Ji J, Jackson DJ, Leache AD, Yang Z. 2023. Power of Bayesian and heuristic tests to detect cross-species introgression with reference to gene flow in the Tamias quadrivittatus group of North American chipmunks. Systematic Biology 72(2):446-465, 10.1093/sysbio/syac077.
Flouri T, Jiao X, Huang J, Rannala B, Yang Z. 2023. Efficient Bayesian inference under the multispecies coalescent with migration, Proc Nat Acad Sci USA, 120: e2310708120.
Álvarez-Carretero S, Tamuri AU, Battini M, Nascimento FF, Carlisle E, Asher RJ, Yang Z, Donoghue PCJ, dos Reis M. 2022. A species-level timeline of mammal evolution integrating phylogenomic data. Nature 602: 263-267 (10.1038/s41586-41021-04341-41581).
Yang, Z. 2014, Molecular Evolution: A Statistical Approach, Oxford University Press (ISBN: 9780199602612).
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Contact us if you have any questions about the Yang Lab.
Yang Lab
Click to email. z.yang@ucl.ac.uk