title: Methods of combinatorial optimization to reveal factors affecting gene length.
abstract: In this paper we present a novel method for genome ranking according to gene lengths. The main outcomes described in this paper are the following: the formulation of the genome ranking problem, presentation of relevant approaches to solve it, and the demonstration of preliminary results from prokaryotic genomes ordering. Using a subset of prokaryotic genomes, we attempted to uncover factors affecting gene length. We have demonstrated that hyperthermophilic species have shorter genes as compared with mesophilic organisms, which probably means that environmental factors affect gene length. Moreover, these preliminary results show that environmental factors group together in ranking evolutionary distant species.
authors.affiliation: Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, Israel. ; Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Bolshoy
authors.forename: Tatiana
authors.initials: T
authors.lastname: Tatarinova
keywords: adaptation; clustering; dimension-reduction techniques; evolution of prokaryotes; factor analysis; machine learning; orthologs; ranking; rating