Genotypic fitness surfaces for the four models of natural selection simulated.

Parameter values used to generate these graphs were α = 12 and s = 0.005. (A) additive, single-optimum (ASO) with a single, most-fit genotype of 12/12. (B) dominant, single-optimum (DSO) where all genotypes 12/_ have a relative fitness of 1.0. (C) addit...

Full description

Saved in:

Bibliographic Details
Main Author:	Ryan J. Haasl (3259872) (author)
Other Authors:	Bret A. Payseur (7310231) (author)
Published:	2024
Subjects:	Genetics Evolutionary Biology Ecology Infectious Diseases Biological Sciences not elsewhere classified xlink "> advances scale analyses like random forests approach population genetic methods modulate gene expression dna sequencing technology selective dynamics navigated microsatellite fitness surfaces influence biological function selection remains uncharacterized characterizing selection assume single nucleotide variants harbor substantial variation fitness landscapes provide approximate bayesian computation fitness landscapes obvious function evolutionary dynamics affect fitness selection strengths natural selection wide scans variants mutate valuable visualization unprecedented scales two parameters specifically designed simple manner report suggests repetitive variants repetitive sequences optimal alleles mutate orders magnitude faster low rate intergenic loci identifying genes examining patterns eight populations easily simulated appreciable percentage 200 humans
Tags:	Add Tag No Tags, Be the first to tag this record!

Genotypic fitness surfaces for the four models of natural selection simulated.

Similar Items