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Approximating fixation probabilities in the generalized Moran process.

Mertzios, G.B. (2014) 'Approximating fixation probabilities in the generalized Moran process.', in Encyclopedia of algorithms. New York: Springer, pp. 1-6.


Problem Definition Population and evolutionary dynamics have been extensively studied, usually with the assumption that the evolving population has no spatial structure. One of the main models in this area is the Moran process [17]. The initial population contains a single “mutant” with fitness r > 0, with all other individuals having fitness 1. At each step of the process, an individual is chosen at random, with probability proportional to its fitness. This individual reproduces, replacing a second individual, chosen uniformly at random, with a copy of itself. Lieberman, Hauert, and Nowak introduced a generalization of the Moran process, where the members of the population are placed on the vertices of a connected graph which is, in general, directed [13, 19]. In this model, the initial population again consists of a single mutant of fitness r > 0 placed on a vertex chosen uniformly at ...

Item Type:Book chapter
Keywords:Evolutionary dynamics, Moran process, Fixation probability, Markov-chain Monte Carlo, Approximation algorithm.
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
File format - PDF (Copyright agreement prohibits open access to the full-text)
Publisher Web site:
Date accepted:03 October 2013
Date deposited:23 June 2015
Date of first online publication:2015
Date first made open access:No date available

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