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.
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Acknowledgements
KD gratefully acknowledge the financial support from CSIR (file number 09/921 (0070)/2012-EMR-I), India. The part of the work done by BD is financially supported by the project National Network for Mathematical and Computational Biology (SERB/F/4931/2013-14) funded by SERB, India. The authors are thankful to Ravi Kumar Singh for tree construction, as well as to Partho Sarothi Ray for helping to prepare the manuscript.
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[Deyasi K, Banerjee A and Deb B 2015 Phylogeny of metabolic networks: A spectral graph theoretical approach. J. Biosci.] DOI 10.1007/s12038-015-9562-0
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Deyasi, K., Banerjee, A. & Deb, B. Phylogeny of metabolic networks: A spectral graph theoretical approach. J Biosci 40, 799–808 (2015). https://doi.org/10.1007/s12038-015-9562-0
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DOI: https://doi.org/10.1007/s12038-015-9562-0