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URN: urn:nbn:de:kobv:517-opus-44975
URL: http://opus.kobv.de/ubp/volltexte/2010/4497/


Ebenhöh, Oliver ; Handorf, Thomas

Functional classification of genome-scale metabolic networks

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Kurzfassung auf Englisch

We propose two strategies to characterize organisms with respect to their metabolic capabilities. The first, investigative, strategy describes metabolic networks in terms of their capability to utilize different carbon sources, resulting in the concept of carbon utilization spectra. In the second, predictive, approach minimal nutrient combinations are predicted from the structure of the metabolic networks, resulting in a characteristic nutrient profile. Both strategies allow for a quantification of functional properties of metabolic networks, allowing to identify groups of organisms with similar functions. We investigate whether the functional description reflects the typical environments of the corresponding organisms by dividing all species into disjoint groups based on whether they are aerotolerant and/or photosynthetic. Despite differences in the underlying concepts, both measures display some common features. Closely related organisms often display a similar functional behavior and in both cases the functional measures appear to correlate with the considered classes of environments. Carbon utilization spectra and nutrient profiles are complementary approaches toward a functional classification of organism-wide metabolic networks. Both approaches contain different information and thus yield different clusterings, which are both different from the classical taxonomy of organisms. Our results indicate that a sophisticated combination of our approaches will allow for a quantitative description reflecting the lifestyles of organisms.

Institut: Institut für Biochemie und Biologie
DDC-Sachgruppe: Biowissenschaften, Biologie
Dokumentart: c Postprint
Schriftenreihe: Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe, ISSN 1866-8372
Band Nummer: paper 129
Quelle: EURASIP (2009), Art. ID 570456, DOI: 10.1155/2009/570456
Sprache: Englisch
Erstellungsjahr: 2009
Publikationsdatum: 16.07.2010
Bemerkung:
The article was originally published by Hindawi Publishing Corporation:
EURASIP : Journal on Bioinformatics and Systems Biology. - (2009), Art. ID 570456 (13 S.)
ISSN 1687-4145
DOI 10.1155/2009/570456
Lizenz: Dieses Werk ist unter einer Creative Commons-Lizenz lizenziert.
Lizenz-Logo  Creative Commons - Attribution 3.0 unported


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