Szczegóły publikacji
Opis bibliograficzny
Clustering organisms using metabolic networks / Tomasz ARODŹ // W: Computational Science – ICCS 2008 : 8th International Conference : Kraków, June 23–25, 2008 : proceedings, Pt. 2 / eds. Marian Bubak, Geert Dick van Albada, Jack Dongarra, Peter M. A. Sloot. — Berlin ; Heidelberg : Springer-Verlag, cop. 2008. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 5102). — ISBN: 978-3-540-69386-4; ISBN: 3-540-69-386-6; e-ISBN: 978-3-540-69387-1. — S. 527–534. — Bibliogr. s. 534, Abstr.
Autor
Dane bibliometryczne
| ID BaDAP | 40277 |
|---|---|
| Data dodania do BaDAP | 2008-09-25 |
| Rok publikacji | 2008 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Czasopisma/serie | Theoretical Computer Science and General Issues, Lecture Notes in Computer Science |
Abstract
Topological properties of metabolic networks may reflect systematic differences between evolutionary distinct groups of organisms. Indeed, the mean shortest path length between metabolites is, on average, longer in eukaryotes than in bacteria. We show that not only the averages of groups differ, but the organisms can be successfully clustered, based on network properties, into categories corresponding to taxonomic groups. We use the fact that in metabolic networks of different organisms, correspondence between vertices is available. We compare our approach with several graph indices employed previously to analyse metabolic networks, and show that they fail at achieving level of clustering similar to ours. Finally, we show that the phylogenetic tree constructed using network-based approach agrees in most cases with gene-based phylogeny.