Empirical profile mixture models for phylogenetic reconstruction | Zendy

Si Quang Le | Zendy; Olivier Gascuel | Zendy; Nicolas Lartillot | Zendy

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Empirical profile mixture models for phylogenetic reconstruction

Author(s) -

Si Quang Le,

Olivier Gascuel,

Nicolas Lartillot

Publication year - 2008

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btn445

Subject(s) - computer science , bayesian probability , phylogenetic tree , expectation–maximization algorithm , context (archaeology) , robustness (evolution) , data mining , set (abstract data type) , maximization , machine learning , maximum likelihood , artificial intelligence , mathematics , statistics , biology , mathematical optimization , programming language , paleontology , biochemistry , gene

Previous studies have shown that accounting for site-specific amino acid replacement patterns using mixtures of stationary probability profiles offers a promising approach for improving the robustness of phylogenetic reconstructions in the presence of saturation. However, such profile mixture models were introduced only in a Bayesian context, and are not yet available in a maximum likelihood (ML) framework. In addition, these mixture models only perform well on large alignments, from which they can reliably learn the shapes of profiles, and their associated weights.

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