Robust classifying of prokaryotic genomes

Authors:
Katerina Korenblat;Zeev Volkovich;Alexander Bolshoy
Affiliations:
Software Engineering Department, ORT Braude Academic College, Karmiel, Israel;Software Engineering Department, ORT Braude Academic College, Karmiel, Israel;Department of Evolutionary and Environmental Biology, University of Haifa, Haifa 31905, Israel
Venue:
Computational Biology and Chemistry
Year:
2012

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Abstract

In this paper, we propose a method to classify prokaryotic genomes using the agglomerative information bottleneck method for unsupervised clustering. Although the method we present here is closely related to a group of methods based on detecting the presence or absence of genes, our method is different because it uses gene lengths as well. We show that this amended method is reliable. For robustness evaluation, we apply bootstrap and jackknife techniques to input data. As a result, we are able to propose an approach to determine the stability level of a cladogram. We demonstrate that the genome tree produced for a selected small group of genomes looks a lot like a phylogenetic tree of this group.