A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach.

By Simon Whelan, Nick Goldman. 2001

2,832 citations recorded by the source corpus.

How researchers see this paper

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

In Genetics

In Molecular Biology

Citations in the corpus

MRFalign: Protein Homology Detection through Alignment of Markov Random Fields (2014, background): “Sequence-based protein alignment and homology detection has been extensively studied and widely applied to many biological problems such as homology modeling [1-4], phylogeny inference [5-7] and protein function prediction [8-10].”
Estimating maximum likelihood phylogenies with PhyML. (2009, neutral): “PhyML implements a wide range of substitution models: JC69 (10), K80 (11), F81 (1), F84 (12), HKY85 (13), TN93 (14) GTR (15, 16) and CUSTOM for nucleotides ; WAG (17), Dayhoff (18), JTT (19), Blosum62 (20), mtREV (21), rtREV (22), cpREV (23), DCMut (24), VT (25) and mtMAM (26) for amino acids.”
Comprehending crystalline β-carotene accumulation by comparing engineered cell models and the natural carotenoid-rich system of citrus (2011, neutral): “, 2005) and was found to be WAG (Whelan and Goldman, 2001) with gamma distributed rates.”
ClipKIT: A multiple sequence alignment trimming software for accurate phylogenomic inference (2020, methodology): “For nucleotide sequences, we used a GTR substitution model [27] with empirical base frequencies and a discrete Gamma model with 4 rate categories [28] or “GTR+F+G”; for amino acid sequences, we used the general WAG model of substitutions [26] with empirical base frequencies and a discrete Gamma mode”
Taxon sampling and the accuracy of phylogenetic analyses (2008, background): “…of model assumptions (e.g., not accurately modeling multiple substitutions), finding a better-fitting model could solve the problem (Olsen, 1987; Whelan & Goldman, 2001; Lartillot & Philippe, 2004; Anderson & Swofford, 2004; Delsuc et al., 2005; Baurain et al., 2007; Lartillot et al., 2007).”
Computing Bayes factors using thermodynamic integration. (2006, methodology): “They account for unequal rates of substitution among amino acids through general time-reversible matrices determined empirically or directly inferred from the data (Jones et al., 1992; Whelan and Goldman, 2001).”
PANTHER: Making genome‐scale phylogenetics accessible to all (2021, methodology): “The probabilistic reconstruction is performed under the WAG substitution model 33 using PAML, 34 and is used in the PANTHER PSEP tool described below.”
ProtTest: selection of best-fit models of protein evolution (2005, methodology): “In this way, different empirical matrices with ﬁxed relative rates of amino acid replacement have been already proposed, like the Dayhoff matrix (Dayhoff et al ., 1978), the JTT matrix (Jones et al ., 1992), the mtREV matrix (Adachi and Hasegawa, 1996) or the WAG matrix (Whelan and Goldman, 2001).”
Bayesian analysis of elapsed times in continuous‐time Markov chains (2008, methodology): “Experts either fix φ to empirically estimated quantities derived from large databases, such as the PAM (Dayhoff et al., 1972), JTT (Jones et al., 1992), and WAG (Whelan and Goldman, 2001) models for amino acid chains, or can provide well-informed priors.”
pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree (2010, methodology): “When analyzing protein sequences the user can choose between the LG [18] or WAG [46] models, and nucleotide likelihoods are computed via the general time reversible (GTR) model.”
Suppression of long-branch attraction artefacts in the animal phylogeny using a site-heterogeneous model (2007, neutral): “By Bayes factor evaluation, we have shown previously that CAT generally has a better fit than homogeneous models based on one single empirical substitution matrix, such as WAG [39], JTT [40], or even the most general site-homogeneous and time-reversible model (GTR) [31,41].”
TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing (2002, methodology): “, 1992), mtREV24 (Adachi and Hasegawa, 1996), BLOSUM 62 (Henikoff and Henikoff, 1992), VT (Müller and Vingron, 2000), WAG (Whelan and Goldman, 2001).”
aLeaves facilitates on-demand exploration of metazoan gene family trees on MAFFT sequence alignment server with enhanced interactivity (2013, methodology): “For distance calculation in this step, several measures can be selected: the Poisson correction (25), maximum-likelihood (ML) estimation with the JTT model (26) and ML estimation with the WAG model (27).”
Class of multiple sequence alignment algorithm affects genomic analysis. (2013, methodology): “Each alignment was translated to amino acids (if necessary), and RAxML (Stamatakis 2006) was used to infer a phylogenetic tree estimate under the WAG + (cid:2) model (Whelan and Goldman 2001).”
Detecting and overcoming systematic errors in genome-scale phylogenies. (2007, methodology): “MrBayes analyses were performed with the WAG amino acid replacement matrix (Whelan and Goldman, 2001), gamma-distributed rates across sites (four discrete categories), and stationary amino acid frequencies estimated from the data set (WAG+F+F4 model).”
Tunicates and not cephalochordates are the closest living relatives of vertebrates (2006, positive): “…both P HYML 9 with either a BIONJ or a user-defined starting tree and T REE F INDER 10 were used to obtain ML trees under a concatenated model assuming the WAG amino acid substitution matrix 11 , ML estimation of amino acid frequencies, plus a gamma distribution with four categories (WAG+F+ Γ 4 ).”
Plasmodium falciparum Erythrocyte Membrane Protein 1 Diversity in Seven Genomes – Divide and Conquer (2010, methodology): “WAG and JTT [114] were found to be the most likely substitution models by fitting of models implemented in RAxML to fixed trees built from the different domain alignments and subsequent ML comparison.”
THE ROLE AND EVOLUTION OF SUPEROXIDE DISMUTASES IN ALGAE 1 (2005, methodology): “In the Bayesian inference we employed a mixed fixed rate estimator and the final model used was the WAG model (Whelan and Goldman, 2001).”