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Updated: May 17, 2026

In Vivo Modeling of the Morbid Human Genome using Danio rerio
Published on: August 24, 2013
Fitness inference tested by in silico population genetics
Hong-Li Zeng1, Yu-Han Huang1, Erik Aurell2
1National Laboratory of Solid State Microstructures, Nanjing University of Posts and Telecommunications, School of Science, Nanjing University, Nanjing 210093, China and Key Laboratory of Radio and Micro-Nano Electronics of Jiangsu Province, Nanjing 210023, China.
None:
We consider populations evolving according to natural selection, mutation, and recombination and assume that the genomes of all or a representative selection of individuals are known. We pose the problem of whether it is possible to infer fitness parameters and genotype fitness order from such data. We tested this hypothesis in simulated populations. We delineate parameter ranges where this is possible and other ranges where it is not. Our work provides a framework for determining when fitness inference is feasible from population-wide, whole-genome, time-stratified data and highlights settings where it is not. We give a brief survey of biological model organisms and human pathogens that fit into this framework.
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