Publications (26) View all
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Article: A systematic survey of the response of a model NF-κB signalling pathway to TNFα stimulation.
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ABSTRACT: White's lab established that strong, continuous stimulation with tumour necrosis factor-α (TNFα) can induce sustained oscillations in the subcellular localisation of the transcription factor nuclear factor κB (NF-κB). But the intensity of the TNFα signal varies substantially, from picomolar in the blood plasma of healthy organisms to nanomolar in diseased states. We report on a systematic survey using computational bifurcation theory to explore the relationship between the intensity of TNFα stimulation and the existence of sustained NF-κB oscillations. Using a deterministic model developed by Ashall et al. in 2009, we find that the system's responses to TNFα are characterised by a supercritical Hopf bifurcation point: above a critical intensity of TNFα the system exhibits sustained oscillations in NF-kB localisation. For TNFα below this critical value, damped oscillations are observed. This picture depends, however, on the values of the model's other parameters. When the values of certain reaction rates are altered the response of the signalling pathway to TNFα stimulation changes: in addition to the sustained oscillations induced by high-dose stimulation, a second oscillatory regime appears at much lower doses. Finally, we define scores to quantify the sensitivity of the dynamics of the system to variation in its parameters and use these scores to establish that the qualitative dynamics are most sensitive to the details of NF-κB mediated gene transcription.Journal of Theoretical Biology 12/2011; 297:137-47. · 2.21 Impact Factor -
Article: Maximin and Bayesian robust experimental design for measurement set selection in modelling biochemical regulatory systems
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ABSTRACT: Experimental design is important in system identification, especially when the models are complex and the measurement data are sparse and noisy, as often occurs in modelling of biochemical regulatory networks. The quality of conventional optimal experimental design largely depends on the accuracy of model parameter estimation, which is often either unavailable or poorly estimated at the stage of design. Robust experimental design (RED) algorithms have thus been proposed when model parametric uncertainties need to be addressed during the design process. In this paper, two robust design strategies are investigated and the comparative study has been made on signal pathway models. The first method is a maximin experimental design approach which is a worst-case design strategy, and the second method is the Bayesian experimental design that ‘takes an average’ of the parametric uncertainty effects. The limitations of the maximin design which describes the structural uncertainty using a local Taylor representation are quantitatively evaluated. To better quantitatively assess the differences between the maximin and the Bayesian REDs, a concept of effective design parameters is proposed, from which the advantages of the Bayesian design is demonstrated especially in the case of large model uncertainties. Copyright © 2010 John Wiley & Sons, Ltd.International Journal of Robust and Nonlinear Control 03/2010; 20(9):1059 - 1078. · 1.55 Impact Factor -
Conference Proceeding: Sensitivity analysis and parameter estimation of signal transduction pathways model
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ABSTRACT: Due to the high nonlinearity in system models, the large number of kinetics parameters involved, the inadequate measurement data in experiments and the noise pollution, etc., parameter estimation is therefore a challenging problem in systems biology. In this work, sensitivity analysis of model output with respect to model parameters is evaluated using Latin hypercube sampling method. Then, a new objective function is proposed based on the probability density function (PDF) of the system output, and particle swarm optimization is used to optimize the objective function through particles' cooperation and evolution. Taking NF-kappaB signal pathways model as an example, this method is applied to rank importance of parameters and to estimate the unknown sensitive parameters for complex signal transduction pathways model. The simulation results show the effectiveness of this new algorithm.Asian Control Conference, 2009. ASCC 2009. 7th; 09/2009 -
Article: [Estimating the parameters of signal transduction pathways with Levenberg-Marquardt algorithm].
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ABSTRACT: The modeling of signal transduction pathways is a task of systems biology. However, such a task is very difficult because of the structure complexity, the strong nonlinearity of signaling pathways and the noised and incomplete measurements. The Levenberg-Marquardt algorithm (LM algorithm) is applied to estimate the unknown parameters of the signaling pathways. With this method, the identifiability of unknown parameters is appraised, and the sensitivity equations of original model are evaluated. Then we append the sensitivity equations to the original model in order to form the augmented model, and we apply the Levenberg-Marquardt algorithm to the augmented model in order to estimate parameters. TNFalpha mediated NF-kappaB signaling pathway is taken as an example to illustrate the effectiveness of this method, and the simulation results are given.Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi 03/2009; 26(1):22-9. -
Article: Sensitivity analysis and robust experimental design of a signal transduction pathway system
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ABSTRACT: Experimental design for cellular networks based on sensitivity analysis is studied in this work. Both optimal and robust experimental design strategies are developed for the IkappaB-NF-kappaB signal transduction model. Based on local sensitivity analysis, the initial IKK intensity is calculated using an optimal experimental design process, and several scalarization measures of the Fisher information matrix are compared. Global sensitivity analysis and robust experimental design techniques are then developed to consider parametric uncertainties in the model. The modified Morris method is employed in global sensitivity analysis, and a semidefinite programming method is exploited to implement the robust experimental design for the problem of measurement set selection. The parametric impacts on the oscillatory behavior of NF-kappaB in the nucleus are also discussed. © 2008 Wiley Periodicals, Inc. Int J Chem Kinet 40: 730-741, 2008International Journal of Chemical Kinetics 09/2008; 40(11):730-741. · 1.01 Impact Factor
