Empirical fitness landscapes reveal accessible evolutionary paths
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DOI: 10.1038/nature05451
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Cited by:
- Krishnendu Chatterjee & Andreas Pavlogiannis & Ben Adlam & Martin A Nowak, 2014. "The Time Scale of Evolutionary Innovation," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-7, September.
- Beerenwinkel Niko & Knupfer Patrick & Tresch Achim, 2011. "Learning Monotonic Genotype-Phenotype Maps," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-27, January.
- Gilpin, William & Feldman, Marcus W., 2019. "Cryptic selection forces and dynamic heritability in generalized phenotypic evolution," Theoretical Population Biology, Elsevier, vol. 125(C), pages 20-29.
- Alicia Sanchez-Gorostiaga & Djordje Bajić & Melisa L Osborne & Juan F Poyatos & Alvaro Sanchez, 2019. "High-order interactions distort the functional landscape of microbial consortia," PLOS Biology, Public Library of Science, vol. 17(12), pages 1-34, December.
- Manhart, Michael & Haldane, Allan & Morozov, Alexandre V., 2012. "A universal scaling law determines time reversibility and steady state of substitutions under selection," Theoretical Population Biology, Elsevier, vol. 82(1), pages 66-76.
- Roger D Kouyos & Gabriel E Leventhal & Trevor Hinkley & Mojgan Haddad & Jeannette M Whitcomb & Christos J Petropoulos & Sebastian Bonhoeffer, 2012. "Exploring the Complexity of the HIV-1 Fitness Landscape," PLOS Genetics, Public Library of Science, vol. 8(3), pages 1-9, March.
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