TY - JOUR

T1 - Dynamical and topological robustness of the mammalian cell cycle network

T2 - A reverse engineering approach

AU - Ruz, Gonzalo A.

AU - Goles, Eric

AU - Montalva, Marco

AU - Fogel, Gary B.

N1 - Funding Information:
The authors would like to thank Conicyt-Chile under grant Fondecyt 11110088 (G.A.R.), Fondecyt 1100003 (E.G.), Fondecyt 3130466 (M.M.), Basal(Conicyt)-CMM , and ANILLO ACT-88 for financially supporting this research.

PY - 2014/1

Y1 - 2014/1

N2 - A common gene regulatory network model is the threshold Boolean network, used for example to model the Arabidopsis thaliana floral morphogenesis network or the fission yeast cell cycle network. In this paper, we analyze a logical model of the mammalian cell cycle network and its threshold Boolean network equivalent. Firstly, the robustness of the network was explored with respect to update perturbations, in particular, what happened to the attractors for all the deterministic updating schemes. Results on the number of different limit cycles, limit cycle lengths, basin of attraction size, for all the deterministic updating schemes were obtained through mathematical and computational tools. Secondly, we analyzed the topology robustness of the network, by reconstructing synthetic networks that contained exactly the same attractors as the original model by means of a swarm intelligence approach. Our results indicate that networks may not be very robust given the great variety of limit cycles that a network can obtain depending on the updating scheme. In addition, we identified an omnipresent network with interactions that match with the original model as well as the discovery of new interactions. The techniques presented in this paper are general, and can be used to analyze other logical or threshold Boolean network models of gene regulatory networks.

AB - A common gene regulatory network model is the threshold Boolean network, used for example to model the Arabidopsis thaliana floral morphogenesis network or the fission yeast cell cycle network. In this paper, we analyze a logical model of the mammalian cell cycle network and its threshold Boolean network equivalent. Firstly, the robustness of the network was explored with respect to update perturbations, in particular, what happened to the attractors for all the deterministic updating schemes. Results on the number of different limit cycles, limit cycle lengths, basin of attraction size, for all the deterministic updating schemes were obtained through mathematical and computational tools. Secondly, we analyzed the topology robustness of the network, by reconstructing synthetic networks that contained exactly the same attractors as the original model by means of a swarm intelligence approach. Our results indicate that networks may not be very robust given the great variety of limit cycles that a network can obtain depending on the updating scheme. In addition, we identified an omnipresent network with interactions that match with the original model as well as the discovery of new interactions. The techniques presented in this paper are general, and can be used to analyze other logical or threshold Boolean network models of gene regulatory networks.

KW - Bees algorithm

KW - Boolean networks

KW - Gene regulatory networks

KW - Threshold networks

KW - Topology robustness

KW - Update robustness

UR - http://www.scopus.com/inward/record.url?scp=84888085635&partnerID=8YFLogxK

U2 - 10.1016/j.biosystems.2013.10.007

DO - 10.1016/j.biosystems.2013.10.007

M3 - Article

C2 - 24212100

AN - SCOPUS:84888085635

SN - 0303-2647

VL - 115

SP - 23

EP - 32

JO - BioSystems

JF - BioSystems

IS - 1

ER -