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Genetic code optimality studied by means of simulated evolution and within the coevolution theory of the canonical code organization

, and . Natural Computing: an international journal, 8 (4): 719--738 (2009)
DOI: http://dx.doi.org/10.1007/s11047-008-9092-x

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Simulated evolution applied to study the genetic code optimality using a model of codon reassignments., and . BMC Bioinformatics, (2011)Evolutionary Optimization of Cancer Treatments in a Cancer Stem Cell Context., and . GECCO, page 233-240. ACM, (2015)Study of Cancer Hallmarks Relevance Using a Cellular Automaton Tumor Growth Model., and . PPSN (1), volume 7491 of Lecture Notes in Computer Science, page 489-499. Springer, (2012)A Cellular Automaton Model for Tumor Growth Simulation., and . PACBB, volume 154 of Advances in Intelligent and Soft Computing, page 147-155. Springer, (2012)Simulated Evolution of the Adaptability of the Genetic Code Using Genetic Algorithms, and . IWINAC '07: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I, page 478--487. Berlin, Heidelberg, Springer-Verlag, (2007)Genetic code optimality studied by means of simulated evolution and within the coevolution theory of the canonical code organization, and . Natural Computing: an international journal, 8 (4): 719--738 (2009)Simulated evolution applied to study the genetic code optimality using a model of codon reassignments, and . BMC Bioinformatics, 12 (1): 56+ (2011)Genetic code optimality studied by means of simulated evolution and within the coevolution theory of the canonical code organization., and . Nat. Comput., 8 (4): 719-738 (2009)Simulated Evolution of the Adaptability of the Genetic Code Using Genetic Algorithms., and . IWINAC (1), volume 4527 of Lecture Notes in Computer Science, page 478-487. Springer, (2007)Cancer Stem Cell Modeling Using a Cellular Automaton., and . IWINAC (2), volume 7931 of Lecture Notes in Computer Science, page 21-31. Springer, (2013)