A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process.

By Nicolas Lartillot, Hervé Philippe. Molecular biology and evolution, 2004

1,485 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Materials Chemistry

View Paper: https://www.semanticscholar.org/paper/d885297790a5d587684d00b4a9a853e5e6d78394

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Citations in the corpus

The influence of rate heterogeneity among sites on the time dependence of molecular rates. (2012, background): “However, more general mixture-models have recently been shown to outperform the discrete gamma model, particularly when multi-modal heterogeneity is present (Lartillot and Philippe 2004; Pagel and Meade 2004; Huelsenbeck and Suchard 2007).”
bModelTest: Bayesian phylogenetic site model averaging and model comparison (2015, methodology): “The CAT-GTR model [10, 11] solves a related problem by providing a mixture model over sites that often fits better than using any single model for all sites.”
Pitfalls in supermatrix phylogenomics (2017, positive): “…bias among unrelated species, and (5) the modelling of the non-homogeneity of the substitution process across sites (mixture models such as CAT; Lartillot & Philippe 2004; Pagel & Meade 2004) by locally decreasing the effective size of the alphabet, which allowed the inference of more…”
Phylotranscriptomic analysis of the origin and early diversification of land plants (2014, methodology): “However, placement of Gnetales as sister to Pinaceae in most supermatrix analyses is consistent with previously published analyses of concatenated gene alignments that explicitly aimed to reduce long-branch attraction artifacts by filtering the most rapidly evolving sites (93, 95, 96) or implementin”
Detecting and overcoming systematic errors in genome-scale phylogenies. (2007, methodology): “We demonstrate that (i) variations in taxon sampling, (ii) removal of fast-evolving sites, (iii) use of a site-heterogeneous mixture model (Lartillot and Philippe, 2004), and (iv) amino acid coding into functional categories have the potential to overcome some types of systematic errors in genome-sc”
A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data. (2004, background): “More recently, Lartillot and Philippe (2004) develop a mixture model for amino acid sequences that allows the equilibrium distribution of amino acid frequencies to vary among sites.”
Molecular phylogenetics: principles and practice (2012, background): “It combines the information in the prior and in the data (likelihood). for the model to accommodate variable amino acid sub-stitution rates among sites 56 or even different amino acid frequencies among sites 57,58 .”
Phylogenomics revives traditional views on deep animal relationships. (2009, methodology): “To analyze our phylogenomic data set, we used the CAT model [14] with PhyloBayes version 2.”
Incorporating molecular evolution into phylogenetic analysis, and a new compilation of conserved polymerase chain reaction primers for animal mitochondrial DNA (2006, background): “Lartillot & Philippe (2004) developed a mixture model for amino acid sequence evolution.”