A Comparison of Models to Infer the Distribution of Fitness Effects of New Mutations
By A. Kousathanas, Peter D. Keightley. Genetics, 2013
1,252 citations recorded by the source corpus.
Subfields: Genetics, Plant Science
View Paper: https://www.semanticscholar.org/paper/ebcf7ec38cea3001a7a991865d938c842a8f26e0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
- Adrian W. R. Serohijos
- Trevor M. Faske
- A. Eckert
- Joshua G. Schraiber
- Fyodor A. Kondrashov
- Eugene I. Shakhnovich
- Olivier Lichtarge
- M. Menon
In Plant Science
- Joshua G. Schraiber
- Eugene I. Shakhnovich
- Adrian W. R. Serohijos
- Fernando Racimo
- Henrik Kaessmann
- Z. Du
- Christine Lovly
Citations in the corpus
- Merging molecular mechanism and evolution: theory and computation at the interface of biophysics and evolutionary population genetics (2014, background): “Although the DFE has been measured for viruses [30], its measurement in living organisms is difficult and resolution-limited [31].”
- Experimental assay of a fitness landscape on a macroevolutionary scale (2017, background): “Substitutions that occur in evolution have properties vastly different from those of random mutations, which are mostly deleterious 23 .”
- The genomics of local adaptation in trees: are we out of the woods yet? (2017, background): “…the distribution of fitness effects of beneficial mutations is also expected to be exponential (Orr 2003; for more discussion on this aspect, see also Orr 2006; Eyre-Walker & Keightley 2007; Martin & Lenormand 2008, Kopp & Hermisson 2009b; Keightley & Eyre-Walker 2010, Dittmar et al. 2016).”
- Approximation to the Distribution of Fitness Effects across Functional Categories in Human Segregating Polymorphisms (2014, positive): “Thus, assuming two classes of sites may not 76 serve to capture all the relevant information about the DFE (but see [25] for an example of fitting a 77 multimodal DFE to population genetic data and [22,26] for nonparametric approaches to estimating the 78 DFE of new amino-acid changing mutations).”
- A formal perturbation equation between genotype and phenotype determines the Evolutionary Action of protein-coding variations on fitness (2014, background): “These protein-coding variants can affect fitness (Eyre-Walker and Keightley 2007), account for 85% of known disease mutations (Choi et al. 2009), and are associated with more than 2500 ail- ments (Botstein and Risch 2003; Bodmer and Bonilla 2008).”