ArticleJournal of biosciences2015
Phylogeny of metabolic networks: a spectral graph theoretical approach.
Article in Journal of biosciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Large scale evaluation of differences between network-based and pairwise sequence-alignment-based methods of dendrogram reconstruction.PloS one · 2019Article
- Topological assessment of metabolic networks reveals evolutionary information.Scientific reports · 2018Article
- The Genome-Scale Integrated Networks in Microorganisms.Frontiers in microbiology · 2018Review
- Morphologies and phenotypes in Bacillus subtilis biofilms.Journal of microbiology (Seoul, Korea) · 2017Article
- Novel Approach to Classify Plants Based on Metabolite-Content Similarity.BioMed research international · 2017Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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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