Novak, S. (2016). Evolutionary proccesses in variable emvironments. Institute of Science and Technology Austria.

Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., &; Tkadik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. Nature Communications. Nature Publishing Group.https://doi.org/10.1038/ncomms12307 

Barton, N. H. (2016). Data from: How does epistasis influence the response to selection? Dryad.https://doi.org/10.5061/dryad.s5s7r 

Fernandes Redondo, R. A., de Vladar, H., Wodarski, T., &; Bollback, J. P. (2016). Data from evolutionary interplay between structure, energy and epistasis in the coat protein of the =54 phage family. The Royal Society.https://doi.org/10.6084/m9.figshare.4315652.v1 

Ellis, T., &; Field, D. (2016). Repeated gains in yellow and anthocyanin pigmentation in flower colour transitions in the Antirrhineae. Annals of Botany. Oxford University Press.https://doi.org/10.1093/aob/mcw043 

Ellis, T., &; Field, D. (2016). Flower colour data and phylogeny (NEXUS) files. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:34 

Ellis, T. (2016). The role of pollinator-mediated selection in the maintenance of a flower color polymorphism in an Antirrhinum majus hybrid zone. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:TH_526  

Tugrul, M. (2016). Evolution of transcriptional regulatory sequences. Institute of Science and Technology Austria.

Field, D., &; Ellis, T. (2016). Inference of mating patterns among wild snapdragons in a natural hybrid zone in 2012. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:37 

Ellis, T. (2016). Data on pollinator observations and offpsring phenotypes. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:35 

Ellis, T. (2016). Pollinator visitation data for wild Antirrhinum majus plants, with phenotypic and frequency data. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:36 

Tugrul, M. (2016). Experimental Data for Binding Site Evolution of Bacterial RNA Polymerase. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:43 

Paixao, T., Sudholt, D., Heredia, J., &; Trubenova, B. (2015). First steps towards a runtime comparison of natural and artificial evolution. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (pp. 1455–1462). Madrid, Spain: ACM.https://doi.org/10.1145/2739480.2754758 

Barton, N. H., &; Servedio, M. (2015). The interpretation of selection coefficients. Evolution. Wiley.https://doi.org/10.1111/evo.12641 

Paixao, T., Badkobeh, G., Barton, N. H., Çörüf, D., Dang, D., Friedrich, T.,https://doi.org/10.1016/j.jtbi.2015.07.011__Trubenova, B. (2015). Toward a unifying framework for evolutionary processes. https://doi.org/10.1016/j.jtbi.2015.07.011__Journal of Theoretical Biology. Elsevier.https://doi.org/10.1016/j.jtbi.2015.07.011 

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Broadhurst, L., Fifield, G., Vanzella, B., &; Pickup, M. (2015). An evaluation of the genetic structure of seed sources and the maintenance of genetic diversity during establishment of two yellow box (Eucalyptus melliodora) seed-production areas. Australian Journal of Botany. CSIRO.https://doi.org/10.1071/BT15023 

Polechova, J., &; Barton, N. H. (2015). Limits to adaptation along environmental gradients. PNAS. National Academy of Sciences.https://doi.org/10.1073/pnas.1421515112 

Novak, S., &; Cremer, S. (2015). Fungal disease dynamics in insect societies: Optimal killing rates and the ambivalent effect of high social interaction rates. Journal of Theoretical Biology. Elsevier.https://doi.org/10.1016/j.jtbi.2015.02.018 

Priklopil, T., Kisdi, E., &; Gyllenberg, M. (2015). Evolutionarily stable mating decisions for sequentially searching females and the stability of reproductive isolation by assortative mating. Evolution. Wiley.https://doi.org/10.1111/evo.12618 

Keller-Schmidt, S., Tugrul, M., Eguíluz, V., Hernandez Garcia, E., &; Klemm, K. (2015). Anomalous scaling in an age-dependent branching model. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics.https://doi.org/10.1103/PhysRevE.91.022803 

Trubenova, B., Novak, S., &; Hager, R. (2015). Indirect genetic effects and the dynamics of social interactions. PLoS One. Public Library of Science.https://doi.org/10.1371/journal.pone.0126907 

Trubenova, B., Novak, S., &; Hager, R. (2015). Description of the agent based simulations. Public Library of Science.https://doi.org/10.1371/journal.pone.0126907.s003 

Tugrul, M., Paixao, T., Barton, N. H., &; Tkadik, G. (2015). Other fitness models for comparison &; for interacting TFBSs. Public Library of Science.https://doi.org/10.1371/journal.pgen.1005639.s001 

Trubenova, B., Novak, S., &; Hager, R. (2015). Mathematical inference of the results. Public Library of Science.https://doi.org/10.1371/journal.pone.0126907.s001 

Tugrul, M., Paixao, T., Barton, N. H., &; Tkadik, G. (2015). Dynamics of transcription factor binding site evolution. PLoS Genetics. Public Library of Science.https://doi.org/10.1371/journal.pgen.1005639 

Giacobbe, M., Guet, C. C., Gupta, A., Henzinger, T. A., Paixao, T., &; Petrov, T. (2015). Model checking gene regulatory networks. Presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom: Springer.https://doi.org/10.1007/978-3-662-46681-0_47 

Priklopil, T., &; Chatterjee, K. (2015). Evolution of decisions in population games with sequentially searching individuals. Games. MDPI.https://doi.org/10.3390/g6040413 

Kollár, R., Bodova, K., Nosek, J., &; Tomáska, d. (2014). Mathematical model of alternative mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics.https://doi.org/10.1103/PhysRevE.89.032701 

Ezard, T., Prizak, R., &; Hoyle, R. (2014). The fitness costs of adaptation via phenotypic plasticity and maternal effects. Functional Ecology. Wiley-Blackwell.https://doi.org/10.1111/1365-2435.12207 

Weissman, D., &; Hallatschek, O. (2014). The rate of adaptation in large sexual populations with linear chromosomes. Genetics. Genetics Society of America.https://doi.org/10.1534/genetics.113.160705 

Arbilly, M., Weissman, D., Feldman, M., &; Grodzinski, U. (2014). An arms race between producers and scroungers can drive the evolution of social cognition. Behavioral Ecology. Oxford University Press.https://doi.org/10.1093/beheco/aru002 

Trotter, M., Weissman, D., Peterson, G., Peck, K., &; Masel, J. (2014). Cryptic genetic variation can make &;quot;irreducible complexity&;quot; a common mode of adaptation in sexual populations. Evolution. Wiley-Blackwell.https://doi.org/10.1111/evo.12517 

Kelleher, J., Etheridge, A., &; Barton, N. H. (2014). Coalescent simulation in continuous space: Algorithms for large neighbourhood size. Theoretical Population Biology. Academic Press.https://doi.org/10.1016/j.tpb.2014.05.001 

Barton, N. H., Novak, S., &; Paixao, T. (2014). Diverse forms of selection in evolution and computer science. PNAS. National Academy of Sciences.https://doi.org/10.1073/pnas.1410107111 

De Vladar, H., &; Barton, N. H. (2014). Stability and response of polygenic traits to stabilizing selection and mutation. Genetics. Genetics Society of America.https://doi.org/10.1534/genetics.113.159111 

Phadke, S., Paixao, T., Pham, T., Pham, S., &; Zufall, R. (2014). Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila. Journal of Heredity. Oxford University Press.https://doi.org/10.1093/jhered/est063 

Prizak, R., Ezard, T., &; Hoyle, R. (2014). Fitness consequences of maternal and grandmaternal effects. Ecology and Evolution. Wiley-Blackwell.https://doi.org/10.1002/ece3.1150 

Hearn, J., Stone, G., Bunnefeld, L., Nicholls, J., Barton, N. H., &; Lohse, K. (2014). Likelihood-based inference of population history from low-coverage de novo genome assemblies. Molecular Ecology. Wiley-Blackwell.https://doi.org/10.1111/mec.12578 

Novak, S. (2014). Habitat heterogeneities versus spatial type frequency variances as driving forces of dispersal evolution. Ecology and Evolution. Wiley-Blackwell.https://doi.org/10.1002/ece3.1289 

Barton, N. H. (2013). Differentiation. In Encyclopedia of Biodiversity (2nd ed., pp. 508–515). Elsevier.https://doi.org/10.1016/b978-0-12-384719-5.00031-9 

Pickup, M., &; Barrett, S. (2013). The influence of demography and local mating environment on sex ratios in a wind-pollinated dioecious plant. Ecology and Evolution. Wiley-Blackwell.https://doi.org/10.1002/ece3.465 

Barton, N. H., Etheridge, A., Kelleher, J., &; Véber, A. (2013). Genetic hitch-hiking in spatially extended populations. Theoretical Population Biology. Elsevier.https://doi.org/10.1016/j.tpb.2012.12.001 

Barton, N. H., &; Paixao, T. (2013). Can quantitative and population genetics help us understand evolutionary computation? In Proceedings of the 15th annual conference on Genetic and evolutionary computation (pp. 1573–1580). Amsterdam, Netherlands: ACM.https://doi.org/10.1145/2463372.2463568 

Long, H., Paixao, T., Azevedo, R., &; Zufall, R. (2013). Accumulation of spontaneous mutations in the ciliate Tetrahymena thermophila. Genetics. Genetics Society of America.https://doi.org/10.1534/genetics.113.153536 

Paixao, T., &; Barton, N. H. (2013). A variance decomposition approach to the analysis of genetic algorithms. In Proceedings of the 15th annual conference on Genetic and evolutionary computation (pp. 845–852). Amsterdam, Netherlands: ACM.https://doi.org/10.1145/2463372.2463470 

Novak, S., Chatterjee, K., &; Nowak, M. (2013). Density games. Journal of Theoretical Biology. Elsevier.https://doi.org/10.1016/j.jtbi.2013.05.029 

Pickup, M., Wilson, S., Freudenberger, D., Nicholls, N., Gould, L., Hnatiuk, S., &; Delandre, J. (2013). Post-fire recovery of revegetated woodland communities in south-eastern Australia. Austral Ecology. Wiley-Blackwell.https://doi.org/10.1111/j.1442-9993.2012.02404.x 

Barton, N. H., Etheridge, A., Kelleher, J., &; Véber, A. (2013). Inference in two dimensions: Allele frequencies versus lengths of shared sequence blocks. Theoretical Population Biology. Elsevier.https://doi.org/10.1016/j.tpb.2013.03.001 

Kelleher, J., Barton, N. H., &; Etheridge, A. (2013). Coalescent simulation in continuous space. Bioinformatics. Oxford University Press.https://doi.org/10.1093/bioinformatics/btt067