Funneled landscape leads to robustness of cell networks: yeast cell cycle.
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This naturally explains robustness from a physical point of view.The ratio of slope versus roughness of the landscape becomes a quantitative measure of robustness of the network.It provides an optimal criterion for network connections and design.
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Affiliation: Department of Chemistry and Department of Physics, State University of New York at Stony Brook, Stony Brook, New York, United States of America. jin.wang.1@stonybrook.edu
ABSTRACT
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We uncovered the underlying energy landscape for a cellular network. We discovered that the energy landscape of the yeast cell-cycle network is funneled towards the global minimum (G0/G1 phase) from the experimentally measured or inferred inherent chemical reaction rates. The funneled landscape is quite robust against random perturbations. This naturally explains robustness from a physical point of view. The ratio of slope versus roughness of the landscape becomes a quantitative measure of robustness of the network. The funneled landscape can be seen as a possible realization of the Darwinian principle of natural selection at the cellular network level. It provides an optimal criterion for network connections and design. Our approach is general and can be applied to other cellular networks. |
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Mentions: In Figure 4, we construct the free energy versus overlap order parameter Q, F(Q) by making use of the microcanonical ensemble. F(Q) = U – TS. U and S are the potential energy and entropy of the system, respectively. They are given by U = < U > (Q) – and S = S0 (Q) – . Here, <U>(Q) is the average of the potential of U(Q) at each overlap Q; ΔU2(Q) is the variance of potential at each Q; S(Q) is the entropy of the configuration at Q, and S0(Q) is given by S0(Q) = lnΩ(Q); Ω(Q) is the number of the configurational states at particular overlap Q. T is the effective temperature. |
View Article: PubMed Central - PubMed
Affiliation: Department of Chemistry and Department of Physics, State University of New York at Stony Brook, Stony Brook, New York, United States of America. jin.wang.1@stonybrook.edu