Research areas
Group webpage: https://biology.st-andrews.ac.uk/kosiol-lab/
Carolin Kosiol is a Reader in Bioinformatics. She works on problems at the intersection of computer science, maths and evolutionary biology. In particular, she wants to understand how natural selection has shaped the genomes of great apes and how fruit flies can adapt to environmental changes in a few dozen generations. Carolin has studied maths and physics at the University of Mainz in Germany, before doing a Masters in High Performance Computing (MSc, University of Dublin, Trinity College) and attending graduate school in Bioinformatics (PhD, University of Cambridge and EMBL- European Bioinformatics Institute). She did a short postdoc at Cornell University during which she got involved in Genome Analysis Consortia. As a Young Group Leader at the Institute of Population Genetics (Vetmeduni Vienna) she has developed methods that combine phylogenetic and population genetic models.
Carolin’s research focuses on the development of computational methods to investigate adaptation at different time-scales ranging from a few generations in experimental evolution data to studies of population demography to phylogenetic analysis of multiple species. Genomes sequences, both from closely related species and from individuals of the same species, are increasingly available. These large amounts of data offer a great opportunity to study speciation and the evolutionary history of populations, provided they can properly model the process of evolution within and between species simultaneously. Together with her group, Carolin has recently developed evolutionary models that bridge the gap between phylogeny and population genetics by taking polymorphism as well as species data into account. She very much enjoys working with experimentalists on genomic data sets that pose ever new challenges to models.
PhD supervision
- Manel Ait El Hadj
- Omar Ruelas Pacheco
Selected publications
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Open access
Bait-ER: a Bayesian method to detect targets of selection in Evolve-and-Resequence experiments
Barata, C. D. C. B. R., Borges, R. & Kosiol, C., 9 Jan 2023, In: Journal of Evolutionary Biology. 36, 1, p. 29-44 16 p.Research output: Contribution to journal › Article › peer-review
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Open access
Selection on the fly: short-term adaptation to an altered sexual selection regime in Drosophila pseudoobscura
Barata, C., Snook, R. R., Ritchie, M. G. & Kosiol, C., 4 Jul 2023, In: Genome Biology and Evolution. 15, 7, 18 p., evad113.Research output: Contribution to journal › Article › peer-review
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Open access
Nucleotide usage biases distort inferences of the species tree
Borges, R., Boussau, B., Szöllősi, G. J. & Kosiol, C., Jan 2022, In: Genome Biology and Evolution. 14, 1, 13 p., evab290.Research output: Contribution to journal › Article › peer-review
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Open access
Polymorphism‐aware estimation of species trees and evolutionary forces from genomic sequences with RevBayes
Borges, R., Boussau, B., Höhna, S., Pereira, R. J. & Kosiol, C., 22 Sept 2022, (E-pub ahead of print) In: Methods in Ecology and Evolution. Early View, 8 p., 13980.Research output: Contribution to journal › Article › peer-review
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Open access
Consistency and identifiability of the polymorphism-aware phylogenetic models
Borges, R. & Kosiol, C., 7 Feb 2020, In: Journal of Theoretical Biology. 486, p. 1-6 6 p., 110074.Research output: Contribution to journal › Article › peer-review
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Open access
Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity
Schrempf, D., Minh, B. Q., von Haeseler, A. & Kosiol, C., Jun 2019, In: Molecular Biology and Evolution. 36, 6, p. 1294-1301 8 p.Research output: Contribution to journal › Article › peer-review
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Open access
Quantifying GC-biased gene conversion in great ape genomes using polymorphism-aware models
Borges, R., Szöllősi, G. & Kosiol, C., 1 Aug 2019, In: Genetics. 212, 4, p. 1321-1336Research output: Contribution to journal › Article › peer-review
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Open access
Selection acting on genomes
Kosiol, C. & Anisimova, M., 6 Jul 2019, (E-pub ahead of print) Evolutionary genomics: statistical and computational methods. Anisimova, M. (ed.). New York: Humana Press Inc., p. 373-397 25 p. (Methods in Molecular Biology; vol. 1910).Research output: Chapter in Book/Report/Conference proceeding › Chapter
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Open access
The comparative genomics and complex population history of Papio baboons
Rogers, J., Raveendran, M., Harris, R. A., Mailund, T., Leppälä, K., Athanasiadis, G., Schierup, M. H., Cheng, J., Munch, K., Walker, J. A., Konkel, M. K., Jordan, V., Steely, C. J., Beckstrom, T. O., Bergey, C., Burrell, A., Schrempf, D., Noll, A., Kothe, M., Kopp, G. H., & 22 others , 30 Jan 2019, In: Science Advances. 5, 1, 15 p., eaau6947.Research output: Contribution to journal › Article › peer-review
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Open access
Inference in population genetics using forward and backward, discrete and continuous time processes
Bergman, J., Schrempf, D., Kosiol, C. & Vogl, C., 14 Feb 2018, In: Journal of Theoretical Biology. 439, p. 166-180 15 p.Research output: Contribution to journal › Article › peer-review