Browse ORBi by ORBi project

- Background
- Content
- Benefits and challenges
- Legal aspects
- Functions and services
- Team
- Help and tutorials

Robustness-based model validation of an apoptosis signalling network model Schliemann, Monica ; ; Bullinger, Eric in Proceedings of the 16th IFAC Symposium on System Identification, Brussels, Belgium, 11–13 July 2012 (2012) Models of intracellular biochemical reaction networks are difficult to parameterise due to the low number of quantitative time series experimental values. Therefore, model validation or invalidation plays ... [more ▼] Models of intracellular biochemical reaction networks are difficult to parameterise due to the low number of quantitative time series experimental values. Therefore, model validation or invalidation plays an important role, as it allows to check qualitatively whether a model structure is suited or not to reproduce qualitatively the experimental findings. This paper analyses the robustness of an experimentally validated polynomial differential equation model of TNF-induced pro-and anti-apoptotic signalling. The bistability of the median model is shown robust to large single parameter variations. Only two parameters (XIAP and Procaspase-3 production rates) are shown to be fragile, in particular when changed simultaneously. Therefore, the model seems valid from the point of view of robustness analysis of the bistability. Many biological experiments quantify average concentrations or the percentage of viable cells, while other methods such as microscopy-based experiments observe single cells. The integration of single cell and cell population behaviour of TNF-induced pro- and anti-apoptotic signalling has been achieved via a cell ensemble model, whose robustness is also analysed here. We show that within the cell population there are cells with not only quantitative differences, but also qualitative ones. In particular, all cells are not bistable. The degree of robustness applicable for the median cell is expanded to combine mono- and bistable models. This measure, applied solely to the two-dimensional subspace of fragile parameters, is shown to correlate well with the time of death. While robustness of bistability can serve for model validation of the median cell model, it cannot for the model of the cell population. [less ▲] Detailed reference viewed: 33 (5 ULg)Heterogeneity Reduces Sensitivity of Cell Death for TNF-Stimuli Schliemann, Monica ; Bullinger, Eric ; et al in BMC Systems Biology (2011), 5 Background Apoptosis is a form of programmed cell death essential for the maintenance of homeostasis and the removal of potentially damaged cells in multicellular organisms. By binding its cognate ... [more ▼] Background Apoptosis is a form of programmed cell death essential for the maintenance of homeostasis and the removal of potentially damaged cells in multicellular organisms. By binding its cognate membrane receptor, TNF receptor type 1 (TNF-R1), the proinflammatory cytokine Tumor Necrosis Factor (TNF) activates pro-apoptotic signaling via caspase activation, but at the same time also stimulates nuclear factor kappaB (NF-kappaB)-mediated survival pathways. Differential dose-response relationships of these two major TNF signaling pathways have been described experimentally and using mathematical modeling. However, the quantitative analysis of the complex interplay between pro- and anti-apoptotic signaling pathways is an open question as it is challenging for several reasons: the overall signaling network is complex, various time scales are present, and cells respond quantitatively and qualitatively in a heterogeneous manner. Results This study analyzes the complex interplay of the crosstalk of TNF-R1 induced pro- and anti-apoptotic signaling pathways based on an experimentally validated mathematical model. The mathematical model describes the temporal responses on both the single cell level as well as the level of a heterogeneous cell population, as observed in the respective quantitative experiments using TNF-R1 stimuli of different strengths and durations. Global sensitivity of the heterogeneous population was quantified by measuring the average gradient of time of death versus each population parameter. This global sensitivity analysis uncovers the concentrations of Caspase-8 and Caspase-3, and their respective inhibitors BAR and XIAP, as key elements for deciding the cell's fate. A simulated knockout of the NF-kappaB-mediated anti-apoptotic signaling reveals the importance of this pathway for delaying the time of death, reducing the death rate in the case of pulse stimulation and significantly increasing cell-to-cell variability. Conclusions Cell ensemble modeling of a heterogeneous cell population including a global sensitivity analysis presented here allowed us to illuminate the role of the different elements and parameters on apoptotic signaling. The receptors serve to transmit the external stimulus; procaspases and their inhibitors control the switching from life to death, while NF-kappaB enhances the heterogeneity of the cell population. The global sensitivity analysis of the cell population model further revealed an unexpected impact of heterogeneity, i.e. the reduction of parametric sensitivity. [less ▲] Detailed reference viewed: 73 (16 ULg)Identification of biochemical reaction networks using a parameter-free coordinate system Fey, Dirk ; ; Bullinger, Eric in Iglesias, P. A.; Ingalls, B. (Eds.) Control-Theoretic Approaches in Systems Biology (2009) A fundamental step in systems biology is the estimation of kinetic parameters, such as association and dissociation constants. Often, their direct estimation from in-vivo studies on isolated reactions is ... [more ▼] A fundamental step in systems biology is the estimation of kinetic parameters, such as association and dissociation constants. Often, their direct estimation from in-vivo studies on isolated reactions is expensive, time-consuming or even infeasible. Therefore, it is necessary to estimate them from indirect measurements, such as time-series data. This chapter proposes an observer-based parameter estimation methodology particularly suited for biochemical reaction networks in which the reaction kinetics are described by polynomial or rational functions. The parameter estimation is performed in three steps. First, the system is transformed into a new set of coordinates in which the system is parameter-free. This facilitates the design of a standard observer in the second step. Finally, the parameter estimates are obtained in a straight-forward way from the observer states, transforming them back to the original coordinates. The approach is illustrated by an example of a MAP kinase signaling pathway. [less ▲] Detailed reference viewed: 119 (13 ULg)Identiﬁkation biochemischer Reaktionsnetzwerke: Ein beobachterbasierter Ansatz Bullinger, Eric ; ; et al in At-Automatisierungstechnik (2008), 56(5), 269-279 Dynamic models present a fundamental tool in systems biology, but rely on kinetic parameters, such as association and dissociation constants. Their direct estimation from studies on isolated reactions is ... [more ▼] Dynamic models present a fundamental tool in systems biology, but rely on kinetic parameters, such as association and dissociation constants. Their direct estimation from studies on isolated reactions is usually expensive, time-consuming or even infeasible for large models. As a consequence, they must be estimated from indirect measurements, usually in the form of time-series data. We describe an observer-based parameter estimation approach taking the specific structure of biochemical reaction networks into account. Considering reaction kinetics described by polynomial or rational functions, we propose a three step approach. In a first step, the estimation of not directly measured states is decoupled from the estimation of the parameters using a suitable model extension. In a second step, a specially suited nonlinear observer estimates the extended state. Based on the obtained state estimates, the parameter estimates are calculated in a straightforward way in the final step. The applicability of the approach is exemplified considering a simplified model of the circadian rhythm. [less ▲] Detailed reference viewed: 31 (7 ULg)System and control theory furthers the understanding of biological signal transduction Bullinger, Eric ; ; et al in Queinnec, I.; Tarbouriech, S.; Garcia, G. (Eds.) et al Biology and Control Theory: Current Challenges (2008) This article discusses why novel modelling and analysis methods are required for biological systems, presents recent advances and outlines some future challenges. In this respect, the main focus is placed ... [more ▼] This article discusses why novel modelling and analysis methods are required for biological systems, presents recent advances and outlines some future challenges. In this respect, the main focus is placed upon methods for parameter estimation and sensitivity analysis as they are encountered in systems biology. [less ▲] Detailed reference viewed: 38 (3 ULg)Parameter estimation in kinetic reaction models using nonlinear observers is facilitated by model extensions Fey, Dirk ; ; Bullinger, Eric in 17th IFAC World Congress, Seoul, Korea (2008) Detailed reference viewed: 42 (4 ULg)Nonlinear Sensitivity Analysis of Biochemical Reaction Networks, by Bilinear Approximation ; ; Bullinger, Eric in Proc. of the 2nd Foundations of Systems Biology in Engineering FOSBE 2007, 9–12 September, Stuttgart Germany (2007) Detailed reference viewed: 12 (1 ULg)Results towards identifiability properties of biochemical reaction networks ; ; Bullinger, Eric et al in Proc. of the 45th IEEE Conference on Decision and Control, San Diego, USA (2006, December) In this paper we consider the question of parameter identifiability for biochemical reaction networks, as typically encountered in systems biology. Specifically, we are interested in deriving conditions ... [more ▼] In this paper we consider the question of parameter identifiability for biochemical reaction networks, as typically encountered in systems biology. Specifically, we are interested in deriving conditions on the biochemical reaction network and on the measured outputs that guarantee identifiability of the parameters. Taking the specific system structure of biochemical reaction networks into account, we derive sufficient conditions for local parameter identifiability based on a suitable system expansion which does not any more directly depend on the parameters. Rather, as shown, the problem of identifiability can be recast as the question of observability of the (parameter free) expanded system. The conditions derived are exemplified considering a simple example [less ▲] Detailed reference viewed: 21 (2 ULg)A note on stability, robustness and performance of output feedback nonlinear model predictive control ; ; Bullinger, Eric et al in Journal of Process Control (2003), 13(7), 633-644 In recent years. nonlinear model predictive control (NMPC) schemes have been derived that guarantee stability of the closed loop under the assumption of full state information. However, only limited ... [more ▼] In recent years. nonlinear model predictive control (NMPC) schemes have been derived that guarantee stability of the closed loop under the assumption of full state information. However, only limited advances have been made with respect to output feedback in the framework of nonlinear predictive control. This paper combines stabilizing instantaneous state feedback NMPC schemes with high-gain observers to achieve output feedback stabilization. For a uniformly observable MIMO system class it is shown that the resulting closed loop is asymptotically stable. Furthermore, the output feedback NMPC scheme recovers the performance of the state feedback in the sense that the region of attraction and the trajectories of the state feedback scheme can be recovered to any degree of accuracy for large enough observer gains, thus leading to semi-regional results. Additionally, it is shown that the output feedback controller is robust with respect to static sector bounded nonlinear input uncertainties. (C) 2003 Elsevier Ltd. All rights reserved. [less ▲] Detailed reference viewed: 27 (1 ULg)Some further results on adaptive lambda-tracking for linear systems with high relative degree Bullinger, Eric ; ; et al in Proc. of the 2000 American Control Conf. (2000) Several adaptive controllers which universally achieve the so-called lambda -tracking have been proposed in the literature. From a practical point of view, previous results are not usable for systems with ... [more ▼] Several adaptive controllers which universally achieve the so-called lambda -tracking have been proposed in the literature. From a practical point of view, previous results are not usable for systems with a high relative degree because of bad numerical conditioning. The paper presents a modified approach overcoming this numerical problem while achieving the same robust stability properties. Stability and convergence of the adaptation is proven for tracking a large class of reference trajectories. The design of the controller is very simple and intuitive, only few parameters have to be tuned and little structural information about the system to be controlled is needed [less ▲] Detailed reference viewed: 19 (0 ULg) |
||