Inferring Fitness in Finite Populations with Moran-like dynamics

2013/03/19 by Marc Harper, Harper, Marc
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · Social Sciences · #91A22 #Dynamical Systems (math.DS) #Evolution and Genetic Dynamics #Evolutionary Game Theory and Cooperation #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Mathematics #Neural and Evolutionary Computing (cs.NE) #Opinion Dynamics and Social Influence #Populations and Evolution (q-bio.PE)

paper · pdf · doi:10.48550/arxiv.1303.4566

openalex publication_date 2013/03/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Biological fitness is not an observable quantity and must be inferred from population dynamics. Bayesian inference applied to the Moran process and variants yields a robust inference method that can infer fitness in populations evolving via a Moran dynamic and generalizations. Information about fitness is derived solely from birth-events in birth-death and death-birth processes in which selection acts proportionally to fitness, which allows the method to be applied to populations on a network where the network itself may be changing in time. Populations may also be allowed to change size while still allowing estimates for fitness to be inferred.

Citations

• Evolutionary games on graphs
• Matplotlib: A 2D Graphics Environment
• The Neutral Theory of Molecular Evolution

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