Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks

Motivation: Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). Results: In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. Availability: An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. Contact: [email protected] Supplementary information: Supplementary data are are available at Bioinformatics online

Singular Points of Reactive Distillation Systems

For the conceptual design of countercurrently operated reactive distillation columns, fast methods are needed to estimate potential top and bottom products. The possible column bottom product composition can be determined from the stable singular points of a batch reactive reboiler. In a similar manner the top product composition can be obtained from the stable singular points of a batch reactive condenser. Geometrically, the singular points of both batch processes are located on a common potential singular point surface (PSPS) whose trajectory depends on the reaction stoichiometry and the phase equilibria. At the singular points, the PSPS intersects a reaction kinetic surface that is dependent on the reaction rate expression and the phase equilibrium of a reference component. Based on the singularity analysis, a single-feed reactive distillation column can be designed. Several hypothetical and real reaction systems are analyzed to illustrate the singularity analysis and the design procedure. Copyright © 1999–2013 John Wiley & Sons, Inc. All Rights Reserved. [accessed 2013 August 15th