Evolvability is defined as the capacity of a system for adaptive evolution. Evolvability is the ability of a population of organisms to not merely generate genetic diversity, but to generate adaptive genetic diversity, and thereby evolve through natural selection.[1][2][3]
In order for a biological organism to evolve by natural selection, there must be a certain minimum probability that new, heritable variants are beneficial. Random mutations, unless they occur in DNA sequences with no function, are expected to be mostly detrimental. Beneficial mutations are always rare, but if they are too rare, then adaptation cannot occur. Early failed efforts to evolve computer programs by random mutation and selection[4] showed that evolvability is not a given, but depends on the representation of the program as a data structure, because this determines how changes in the program map to changes in its behavior.[5] Analogously, the evolvability of organisms depends on their genotype–phenotype map.[6][7][8] This means that genomes are structured in ways that make beneficial changes more likely. This has been taken as evidence that evolution has created fitter populations of organisms that are better able to evolve.
^Colegrave N, Collins S (May 2008). "Experimental evolution: experimental evolution and evolvability". Heredity. 100 (5): 464–70. doi:10.1038/sj.hdy.6801095. PMID 18212804.
^Kirschner M, Gerhart J (July 1998). "Evolvability". Proceedings of the National Academy of Sciences of the United States of America. 95 (15): 8420–7. Bibcode:1998PNAS...95.8420K. doi:10.1073/pnas.95.15.8420. PMC 33871. PMID 9671692.
^Altenberg L (1995). "Genome growth and the evolution of the genotype–phenotype map". Evolution and Biocomputation. Lecture Notes in Computer Science. Vol. 899. pp. 205–259. CiteSeerX 10.1.1.493.6534. doi:10.1007/3-540-59046-3_11. ISBN 978-3-540-59046-0.
^Friedberg RM (1958). "A Learning Machine: Part I |". IBM Journal of Research and Development. 2 (1): 2–13. doi:10.1147/rd.21.0002.
^Altenberg L (1994). Kinnear, Kenneth (ed.). "The evolution of evolvability in genetic programming". Advances in Genetic Programming: 47–74.
^Wagner GP, Altenberg L (June 1996). "Perspective: Complex adaptations and the evolution of evolvability". Evolution; International Journal of Organic Evolution. 50 (3): 967–976. doi:10.1111/j.1558-5646.1996.tb02339.x. JSTOR 2410639. PMID 28565291. S2CID 21040413.
^Bianco, Simone (April 1, 2022). "Artificial Intelligence: Bioengineers' Ultimate Best Friend". GEN Biotechnology. 1 (2). Mary Ann Liebert: 140–141. doi:10.1089/genbio.2022.29027.sbi. ISSN 2768-1572. S2CID 248313305.
^Vaishnav ED, de Boer CG, Molinet J, Yassour M, Fan L, Adiconis X, Thompson DA, Levine JZ, Cubillos FA, Regev A (March 2022). "The evolution, evolvability and engineering of gene regulatory DNA". Nature. 603 (7901): 455–463. Bibcode:2022Natur.603..455V. doi:10.1038/s41586-022-04506-6. PMC 8934302. PMID 35264797.
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