EREM: Parameter Estimation and Ancestral Reconstruction by Expectation-Maximization Algorithm for a Probabilistic Model of Genomic Binary Characters Evolution. (6th May 2010)

• Record Type: Journal Article
• Authors: Carmel, Liran; Wolf, Yuri I.; Rogozin, Igor B.; Koonin, Eugene V.
• Other Names: Makalowski Wojciech Academic Editor.
• Is Part Of: Advances in bioinformatics. Volume 2010(2010)
• Publication Date: 2010-05-06
• Subjects: Bioinformatics -- Periodicals; Bioinformatics; Computational Biology -- Periodicals; Periodicals; 570.285
• DOI: 10.1155/2010/167408
• Languages: English
• ISSNs: 1687-8027

Abstract

Abstract : Evolutionary binary characters are features of species or genes, indicating the absence (value zero) or presence (value one) of some property. Examples include eukaryotic gene architecture (the presence or absence of an intron in a particular locus), gene content, and morphological characters. In many studies, the acquisition of such binary characters is assumed to represent a rare evolutionary event, and consequently, their evolution is analyzed using various flavors of parsimony. However, when gain and loss of the character are not rare enough, a probabilistic analysis becomes essential. Here, we present a comprehensive probabilistic model to describe the evolution of binary characters on a bifurcating phylogenetic tree. A fast software tool, EREM, is provided, using maximum likelihood to estimate the parameters of the model and to reconstruct ancestral states (presence and absence in internal nodes) and events (gain and loss events along branches).