Mathematical Identification of Critical Reactions in the Interlocked Feedback Model

Dynamic simulations are necessary for understanding the mechanism of how biochemical networks generate robust properties to environmental stresses or genetic changes. Sensitivity analysis allows the linking of robustness to network structure. However, it yields only local properties regarding a particular choice of plausible parameter values, because it is hard to know the exact parameter values in vivo. Global and firm results are needed that do not depend on particular parameter values. We propose mathematical analysis for robustness (MAR) that consists of the novel evolutionary search that explores all possible solution vectors of kinetic parameters satisfying the target dynamics and robustness analysis. New criteria, parameter spectrum width and the variability of solution vectors for parameters, are introduced to determine whether the search is exhaustive. In robustness analysis, in addition to single parameter sensitivity analysis, robustness to multiple parameter perturbation is defined. Combining the sensitivity analysis and the robustness analysis to multiple parameter perturbation enables identifying critical reactions. Use of MAR clearly identified the critical reactions responsible for determining the circadian cycle in the Drosophila interlocked circadian clock model. In highly robust models, while the parameter vectors are greatly varied, the critical reactions with a high sensitivity are uniquely determined. Interestingly, not only the per-tim loop but also the dclk-cyc loop strongly affect the period of PER, although the dclk-cyc loop hardly changes its amplitude and it is not potentially influential. In conclusion, MAR is a powerful method to explore wide parameter space without human-biases and to link a robust property to network architectures without knowing the exact parameter values. MAR identifies the reactions critically responsible for determining the period and amplitude in the interlocked feedback model and suggests that the circadian clock intensively evolves or designs the kinetic parameters so that it creates a highly robust cycle

A Symmetric Dual Feedback System Provides a Robust and Entrainable Oscillator

Many organisms have evolved molecular clocks to anticipate daily changes in their environment. The molecular mechanisms by which the circadian clock network produces sustained cycles have extensively been studied and transcriptional-translational feedback loops are common structures to many organisms. Although a simple or single feedback loop is sufficient for sustained oscillations, circadian clocks implement multiple, complicated feedback loops. In general, different types of feedback loops are suggested to affect the robustness and entrainment of circadian rhythms

A statistical mechanics of an oscillator associative memory with scattered natural frequencies

Analytic treatment of a non-equilibrium random system with large degrees of freedoms is one of most important problems of physics. However, little research has been done on this problem as far as we know. In this paper, we propose a new mean field theory that can treat a general class of a non-equilibrium random system. We apply the present theory to an analysis for an associative memory with oscillatory elements, which is a well-known typical random system with large degrees of freedoms.Comment: 8 pages, 4 figure

Cluster variation method and disorder varieties of two-dimensional Ising-like models

I show that the cluster variation method, long used as a powerful hierarchy of approximations for discrete (Ising-like) two-dimensional lattice models, yields exact results on the disorder varieties which appear when competitive interactions are put into these models. I consider, as an example, the plaquette approximation of the cluster variation method for the square lattice Ising model with nearest-neighbor, next-nearest-neighbor and plaquette interactions, and, after rederiving known results, report simple closed-form expressions for the pair and plaquette correlation functions.Comment: 10 revtex pages, 1 postscript figur

Regional-scale chemical transport modeling in support of the analysis of observations obtained during the TRACE-P experiment

Data obtained during the TRACE-P experiment is used to evaluate how well the CFORS/STEM-2K1 regional-scale chemical transport model is able to represent the aircraft observations. Thirty-one calculated trace gas and aerosol parameters are presented and compared to the in situ data. The regional model is shown to accurately predict many of the important features observed. The mean values of all the model parameters in the lowest 1 km are predicted within ±30% of the observed values. The correlation coefficients (R) for the meteorological parameters are found to be higher than those for the trace species. For example, for temperature, R \u3e 0.98. Among the trace species, ethane, propane, and ozone show the highest values (0.8 \u3c R \u3c 0.9), followed by CO, SO2, and NOy, NO and NO2 had the lowest values (R \u3c 0.4). Analyses of pollutant transport into the Yellow Sea by frontal events are presented and illustrate the complex nature of outflow. Biomass burning from SE Asia is transported in the warm conveyor belt at altitudes above ∼2 km and at latitudes below 30N. Outflow of pollution emitted along the east coast of China in the postfrontal regions is typically confined to the lower ∼2 km and results in high concentrations with plume-like features in the Yellow Sea. During these situations the model underpredicts CO and black carbon (among other species). An analysis of ozone production in this region is also presented. In and around the highly industrialized regions of East Asia, where fossil fuel usage dominates, ozone is NMHC-limited. South of ∼30-35N, ozone production is NOx-limited, reflecting the high NMHC/NOx ratios due to the large contributions to the emissions from biomass burning, biogenics sources, and biofuel usage in central China and SE Asia. Copyright 2003 by the American Geophysical Union

Threshold electronic structure at the oxygen K edge of 3d transition metal oxides: a configuration interaction approach

It has been generally accepted that the threshold structure observed in the oxygen K edge X-ray absorption spectrum in 3d transition metal oxides represents the electronic structure of the 3d transition metal. There is, however, no consensus about the correct description. We present an interpretation, which includes both ground state hybridization and electron correlation. It is based on a configuration interaction cluster calculation using a MO6 cluster. The oxygen K edge spectrum is calculated by annihilating a ligand hole in the ground state and is compared to calculations representing inverse photoemission experiments in which a 3d transition metal electron is added. Clear differences are observed related to the amount of ligand hole created in the ground state. Two "rules" connected to this are discussed. Comparison with experimental data of some early transition metal compounds is made and shows that this simple cluster approach explains the experimental features quite well.Comment: 10 pages, submitted to Phys. Rev. B, tried to make a better PS file

High-pressure synthesis of Ba2RhO4, a rhodate analog of the layered perovskite Sr-ruthenate

A layered perovskite-type oxide Ba2RhO4 was synthesized by a high-pressure technique with the support of convex-hull calculations. The crystal and electronic structure were studied by both experimental and computational tools. Structural refinements for powder x-ray diffraction data showed that Ba2RhO4 crystallizes in a K2NiF4-type structure, isostructural to Sr2RuO4 and Ba2IrO4. Magnetic, resistivity, and specific-heat measurements for polycrystalline samples of Ba2RhO4 indicate that the system can be characterized as a correlated metal. Despite the close similarity to its Sr2RuO4 counterpart in the electronic specific-heat coefficient and the Wilson ratio, Ba2RhO4 shows no signature of superconductivity down to 0.16 K. Whereas the Fermi surface topology has reminiscent pieces of Sr2RuO4, an electronlike eg-(dx2-y2) band descends below the Fermi level, making this compound unique also as a metallic counterpart of the spin-orbit coupled Mott insulator Ba2IrO4