title: Phylogeny of metabolic networks: a spectral graph theoretical approach.
abstract: Many methods have been developed for finding the commonalities between different organisms in order to study their phylogeny. The structure of metabolic networks also reveals valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyse the phylogeny from these distances. In our analysis, we focused on the species that belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.
authors.affiliation: Department of Mathematics and Statistics, Indian Institute of Science Education and Research, Kolkata, Mohanpur 741 246, India.
authors.forename: Krishanu
authors.initials: K
authors.lastname: Deyasi
authors.forename: Anirban
authors.initials: A
authors.lastname: Banerjee
authors.forename: Bony
authors.initials: B
authors.lastname: Deb
mesh_terms: D001105:Archaea / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D001419:Bacteria / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D005075:Biological Evolution; D019295:Computational Biology / Q000379:methods; D017753:Ecosystem; D056890:Eukaryota / Q000145:classification / Q000235:genetics / Q000378:metabolism*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008954:Models, Biological; D010802:Phylogeny