Codon-substitution models for heterogeneous selection pressure at amino acid sites.

By Ziheng Yang, Rasmus Nielsen, Nick Goldman, A. K. Pedersen. Genetics, 2000

2,366 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8d54df6996acbb4c6758544b046278166afa4a9a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

The Sorcerer II Global Ocean Sampling Expedition: Expanding the Universe of Protein Families (2007, methodology): “A likelihood ratio test was applied to select clusters for which M3 explained the data significantly better than M0 [ 136 ].”
RELAX: detecting relaxed selection in a phylogenetic framework. (2014, background): “Therefore, it became conventional to think in terms of the distribution of ! values over sites instead of a single gene-wide ! (Yang et al. 2000).”
Empirical profile mixture models for phylogenetic reconstruction (2008, methodology): “Mixture models have been used several times in phylogenetics, to model variations across sites of various aspects of the substitution or replacement process, such as the dN/dS ratio (Yang et al. , 2000), or even the complete substitution matrix (Koshi and Goldstein, 1998; Pagel and Meade, 2004).”
Model selection in ecology and evolution. (2004, background): “Molecular evolution Understanding the process of nucleotide/protein evolution [ 62 ,63] Molecular systematics Choosing a model of molecular evolution for phylogenetic reconstruction [4,64,65]”
Incorporating molecular evolution into phylogenetic analysis, and a new compilation of conserved polymerase chain reaction primers for animal mitochondrial DNA (2006, methodology): “In addition to the Tuffley & Steel (1998) and Galtier (2001) models cited above, Yang et al. (2000) created a model that allows selection constraints to change across the sequence.”
A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data. (2004, methodology): “Krajewski et al. (1999) attempt to construct a mixture model based upon distance matrices, and Yang et al. (2000) use a mixture model to sum over different values of the synonymous/nonsynonymous substitution ratio at each site.”
An Evolutionary-Network Model Reveals Stratified Interactions in the V3 Loop of the HIV-1 Envelope (2007, background): “Furthermore, previous studies have demonstrated that maximum-likelihood estimates of substitution rates or counts are relatively insensitive to the tree topology [51,77].”
PAML 4: phylogenetic analysis by maximum likelihood. (2007, background): “The site models treats the x ratio for any site (codon) in the gene as a random variable from a statistical distribution, thus allowing x to vary among codons (Nielsen and Yang 1998; Yang et al. 2000).”
The rapid evolution of reproductive proteins (2002, methodology): “If sequences are available from several species, new MAXIMUM-LIKELIHOOD prediction methods can be used to detect selection that acts on a subset of codon”
Three Members of the 6-cys Protein Family of Plasmodium Play a Role in Gamete Fertility (2010, methodology): “using a codon-based model of sequence evolution [45,46], with dN”
Distinguishing importation from diversification of quinolone-resistant Neisseria gonorrhoeae by molecular evolutionary analysis (2007, methodology): “[40] as implemented in the PAML package [41].”
Model selection and model averaging in phylogenetics: advantages of akaike information criterion and bayesian approaches over likelihood ratio tests. (2004, methodology): “Lastly, model averaging could also be applied to other problems in evolutionary biology in which inferences can be drawn from several models, for example as in the detection of positive selection from sequence alignments ( Yang et al., 2000 ), and the estimation of divergence times using relaxed mol”
Accurate extension of multiple sequence alignments using a phylogeny-aware graph algorithm (2012, methodology): “The codon data, analyzed both as DNA and protein, were simulated under purifying selection [model M0 with ω=0.15 (Yang et al., 2000)] and many substitutions were synonymous on the protein level: despite the three-times greater number of sites for DNA, the sequence identity of DNA and protein…”
Selecton 2007: advanced models for detecting positive and purifying selection using a Bayesian inference approach (2007, methodology): “It should be noted that in the first two nested comparisons, nesting is achieved by fixing one of the parameters on the boundary of the parameter space (6,25), requiring caution when comparing the models with an LRT.”