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B. Batut, G. Beslon, and C. Knibbe, Unexpected genome inflation and streamlining in variable environments, Proceedings of Jobim 2016, pp.320-322, 2016.
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B. Batut, G. Beslon, and C. Knibbe, Genome inflation under variable environments, 2016.

E. Colizzi and P. Hogeweg, Evolution of Functional Diversification within Quasispecies, Genome Biology and Evolution, vol.6, issue.8, 2014.
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F. De-boer and P. Hogeweg, Co-evolution and ecosystem based problem solving, Ecological Informatics, vol.9, pp.47-58, 2012.
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V. Cooper, M. Schneider, R. Blot, and . Lenski, Mechanisms Causing Rapid and Parallel Losses of Ribose Catabolism in Evolving Populations of Escherichia coli B, Journal of Bacteriology, vol.183, issue.9, pp.2834-2841, 2001.
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A. Crombach and P. Hogeweg, Chromosome Rearrangements and the Evolution of Genome Structuring and Adaptability, Molecular Biology and Evolution, vol.24, issue.5, pp.1130-1139, 2007.
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T. Cuypers and P. Hogeweg, Virtual Genomes in Flux: An Interplay of Neutrality and Adaptability Explains Genome Expansion and Streamlining, Genome Biology and Evolution, vol.4, issue.3, pp.212-229, 2012.
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F. Fet, Proactive EVLIT program Variability: mechanisms and consequences Project reference: 610427 Version 1

T. Cuypers and P. Hogeweg, A Synergism between Adaptive Effects and Evolvability Drives Whole Genome Duplication to Fixation, PLoS Computational Biology, vol.1, issue.4, 2014.
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B. Van, D. , and P. Hogeweg, Multi-level evolution, differential gene mobility, and the persistence of population diversity, Proceedings of the European Conference on Artificial Life 2015, pp.9-11, 2015.

B. Van-dijk and P. Hogeweg, In Silico Gene-Level Evolution Explains Microbial Population Diversity through Differential Gene Mobility, Genome Biology and Evolution, vol.8, issue.1, pp.176-188, 2016.
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S. Fischer, G. Bernard, C. Beslon, and . Knibbe, A Model for Genome Size Evolution, Bulletin of Mathematical Biology, vol.104, issue.41, pp.2249-2291, 2014.
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S. Hickinbotham and P. Hogeweg, Evolution towards extinction in replicase models: inevitable unless... 2 nd EvoEvo Workshop, 2016.

C. Knibbe and D. Parsons, What happened to my genes? Insights on gene family dynamics from digital genetics experiments, Proceedings of ALIFE 14, pp.33-40, 2014.
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C. Knibbe, D. Schneider, and G. Beslon, evolution without (point) mutations, 2016.

J. Plucain, L. Hindré, . Gac, . Tenaillon, C. Cruveiller et al., Epistasis and Allele Specificity in the Emergence of a Stable Polymorphism in Escherichia coli, Science, vol.6, issue.6, pp.3431366-1369, 2014.
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P. Puigbo, . Lobkovsky, Y. Dm-kristensen, E. Wolf, and . Koonin, Genomes in turmoil: quantification of genome dynamics in prokaryote supergenomes, BMC Biology, vol.9, issue.1, p.66, 2014.
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C. Rocabert, C. Knibbe, and G. Beslon, Towards an Integrated Evolutionary Model to Study Evolution of Evolution, First EvoEvo Workshop, vol.15, 2015.

C. Rocabert, C. Knibbe, D. Consuegra, G. Schneider, and . Beslon, Beware batch culture: Seasonality and niche construction predicted to favor bacterial adaptive diversification, PLOS Computational Biology, vol.69, issue.2, 2016.
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F. Fet, Proactive EVLIT program Variability: mechanisms and consequences Project reference: 610427 Version 1

P. Jp-rutten, G. Hogeweg, and . Beslon, Evolution of mutator populations in constant environments. 2 nd EvoEvo Workshop, 2016.

P. Jp-rutten, G. Hogeweg, and . Beslon, Adapting the engine to the fuel: hypermutator populations can escape the mutational burden by reorganizing their genome structure, 2016.

R. Sanjuan, S. Moya, and . Elena, The distribution of fitness effects caused by singlenucleotide substitutions in an RNA virus, pp.8396-8401, 2004.

N. Takeuchi and P. Hogeweg, Evolution of complexity in RNA-like replicator systems, Biology Direct, vol.3, issue.1, p.11, 2008.
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Y. Vadée-le-brun, J. Rouzaud-cornabas, and G. Beslon, Epigenetic inheritance speeds up evolution of artificial organisms, Proceedings of the European Conference on Artificial Life 2015, pp.439-446, 2015.

Y. Vadée-le-brun, J. Rouzaud-cornabas, and G. Beslon, In Silico Experimental Evolution suggests a complex intertwining of selection, robustness and drift in the evolution of genetic networks complexity, Proceedings of the Artificial Life Conference 2016, pp.180-187, 2016.

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