When metabolism meets topology: Reconciling metabolite and reaction networks.
The search for a systems-level picture of metabolism as a web of molecular interactions provides a paradigmatic example of how the methods used to characterize a system can bias the interpretation of its functional meaning. Metabolic maps have been analyzed using novel techniques from network theory, revealing some non-trivial, functionally relevant properties. These include a small-world structure and hierarchical modularity. However, as discussed here, some of these properties might actually result from an inappropriate way of defining network interactions. Starting from the so-called bipartite organization of metabolism, where the two meaningful subsets (reactions and metabolites) are considered, most current works use only one of the subsets by means of so-called graph projections. Unfortunately, projected graphs often ignore relevant biological and chemical constraints, thus leading to statistical artifacts. Some of these drawbacks and alternative approaches need to be properly addressed.
Montañez
Raul
R
Departamento de Biología Molecular y Bioquímica, Facultad de Ciencias, Universidad de Málaga, E-29071 Málaga, and CIBER de Enfermedades Raras (CIBERER), Málaga, Spain.
Medina
Miguel Angel
MA
Departamento de Biología Molecular y Bioquímica, Facultad de Ciencias, Universidad de Málaga, E-29071 Málaga, and CIBER de Enfermedades Raras (CIBERER), Málaga, Spain.
Solé
Ricard V
RV
ICREA-Complex Systems Lab, Universitat Pompeu Fabra. Parc de Recerca Biomèdica de Barcelona. Dr. Aiguader 88, 08003. Barcelona, Spain.|Santa Fe Institute 1399 Hyde Park Road, Santa Fe, NM 87501, USA.
Rodríguez-Caso
Carlos
C
ICREA-Complex Systems Lab, Universitat Pompeu Fabra. Parc de Recerca Biomèdica de Barcelona. Dr. Aiguader 88, 08003. Barcelona, Spain.
D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D004734:Energy Metabolism; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008954:Models, Biological