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1.  GENOME-WIDE COMPARATIVE ANALYSIS OF PHYLOGENETIC TREES: THE PROKARYOTIC FOREST OF LIFE 
Methods in molecular biology (Clifton, N.J.)  2012;856:10.1007/978-1-61779-585-5_3.
Genome-wide comparison of phylogenetic trees is becoming an increasingly common approach in evolutionary genomics, and a variety of approaches for such comparison have been developed. In this article we present several methods for comparative analysis of large numbers of phylogenetic trees. To compare phylogenetic trees taking into account the bootstrap support for each internal branch, the Boot-Split Distance (BSD) method is introduced as an extension of the previously developed Split Distance (SD) method for tree comparison. The BSD method implements the straightforward idea that comparison of phylogenetic trees can be made more robust by treating tree splits differentially depending on the bootstrap support. Approaches are also introduced for detecting tree-like and net-like evolutionary trends in the phylogenetic Forest of Life (FOL), i.e., the entirety of the phylogenetic trees for conserved genes of prokaryotes. The principal method employed for this purpose includes mapping quartets of species onto trees to calculate the support of each quartet topology and so to quantify the tree and net contributions to the distances between species. We describe the applications methods used to analyze the FOL and the results obtained with these methods. These results support the concept of the Tree of Life (TOL) as a central evolutionary trend in the FOL as opposed to the traditional view of the TOL as a ‘species tree’.
doi:10.1007/978-1-61779-585-5_3
PMCID: PMC3842619  PMID: 22399455
Forest of life; tree of life; phylogenomic methods; tree comparison; map of quartets
2.  A Maximum Likelihood Method for Reconstruction of the Evolution of Eukaryotic Gene Structure 
Spliceosomal introns are one of the principal distinctive features of eukaryotes. Nevertheless, different large-scale studies disagree about even the most basic features of their evolution. In order to come up with a more reliable reconstruction of intron evolution, we developed a model that is far more comprehensive than previous ones. This model is rich in parameters, and estimating them accurately is infeasible by straightforward likelihood maximization. Thus, we have developed an expectation-maximization algorithm that allows for efficient maximization. Here, we outline the model and describe the expectation-maximization algorithm in detail. Since the method works with intron presence–absence maps, it is expected to be instrumental for the analysis of the evolution of other binary characters as well.
doi:10.1007/978-1-59745-243-4_16
PMCID: PMC3410445  PMID: 19381540
Maximum likelihood; expectation-maximization; intron evolution; ancestral reconstruction; eukaryotic gene structure

Results 1-2 (2)