Monotonicity, frustration, and ordered response: an analysis of the energy landscape of perturbed large-scale biological networks.
BACKGROUND
For large-scale biological networks represented as signed graphs, the index of frustration measures how far a network is from a monotone system, i.e., how incoherently the system responds to perturbations.


RESULTS
In this paper we find that the frustration is systematically lower in transcriptional networks (modeled at functional level) than in signaling and metabolic networks (modeled at stoichiometric level). A possible interpretation of this result is in terms of energetic cost of an interaction: an erroneous or contradictory transcriptional action costs much more than a signaling/metabolic error, and therefore must be avoided as much as possible. Averaging over all possible perturbations, however, we also find that unlike for transcriptional networks, in the signaling/metabolic networks the probability of finding the system in its least frustrated configuration tends to be high also in correspondence of a moderate energetic regime, meaning that, in spite of the higher frustration, these networks can achieve a globally ordered response to perturbations even for moderate values of the strength of the interactions. Furthermore, an analysis of the energy landscape shows that signaling and metabolic networks lack energetic barriers around their global optima, a property also favouring global order.


CONCLUSIONS
In conclusion, transcriptional and signaling/metabolic networks appear to have systematic differences in both the index of frustration and the transition to global order. These differences are interpretable in terms of the different functions of the various classes of networks.
SISSA-ISAS, International School for Advanced Studies, Trieste, Italy.
Giovanni
G
Iacono
Claudio
C
Altafini
D000465:Algorithms; D003198:Computer Simulation; D053263:Gene Regulatory Networks; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*; D049490:Systems Biology / Q000379:methods*