Empirical profile mixture models for phylogenetic reconstruction

Bioinformatics. 2008 Oct 15;24(20):2317-23. doi: 10.1093/bioinformatics/btn445. Epub 2008 Aug 21.


Motivation: 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.

Results: In this work, we introduce an expectation-maximization algorithm for estimating amino acid profile mixtures from alignment databases. We apply it, learning on the HSSP database, and observe that a set of 20 profiles is enough to provide a better statistical fit than currently available empirical matrices (WAG, JTT), in particular on saturated data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Amino Acid Sequence
  • Amino Acid Substitution*
  • Animals
  • Bayes Theorem
  • Computational Biology / methods*
  • Databases, Protein
  • Humans
  • Likelihood Functions
  • Phylogeny*
  • Sequence Alignment
  • Sequence Analysis, Protein