Magdeburg, Germany

The Max Planck Institute for Dynamics of Complex Technical Systems is located in Magdeburg, Germany. It was founded in 1996. It is one of 80 institutes in the Max Planck Society . Wikipedia.

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Stoll M.,Max Planck Institute for Dynamics of Complex Technical Systems | Wathen A.,Mathematical Institute
Journal of Computational Physics | Year: 2013

The solution of time-dependent PDE-constrained optimization problems subject to unsteady flow equations presents a challenge to both algorithms and computing power. In this paper we present an all-at-once approach where we solve for all time-steps of the discretized unsteady Stokes problem at once. The most desirable feature of this approach is that for all steps of an iterative scheme we only need approximate solutions of the discretized Stokes operator. This leads to an efficient scheme which exhibits mesh-independent behaviour. © 2012 Elsevier Inc.

Anta A.,Max Planck Institute for Dynamics of Complex Technical Systems | Tabuada P.,University of California at Los Angeles
IEEE Transactions on Automatic Control | Year: 2012

Event-triggered control and self-triggered control have been recently proposed as new implementation paradigms that reduce resource usage for control systems. In self-triggered control, the controller is augmented with the computation of the next time instant at which the feedback control law is to be recomputed. Since these execution instants are obtained as a function of the plant state, we effectively close the loop only when it is required to maintain the desired performance, thereby greatly reducing the resources required for control. In this paper we present a new technique for the computation of the execution instants by exploiting the concept of isochronous manifolds, also introduced in this paper. While our previous results showed how homogeneity can be used to compute the execution instants along some directions in the state space, the concept of isochrony allows us to compute the executions instants along every direction in the state space. Moreover, we also show in this paper how to homogenize smooth control systems thus making our results applicable to any smooth control system. The benefits of the proposed approach with respect to existing techniques are analyzed in two examples. © 2011 IEEE.

Straube R.,Max Planck Institute for Dynamics of Complex Technical Systems
Science Signaling | Year: 2012

Jiang et al. (Research Article, 11 October 2011, DOI: 10.1126/scisignal. 2002152) used a combined experimental and computational modeling approach to study the dynamic response behavior of covalent modification cycles in the presence of downstream targets ("loads"). Despite remarkable agreement between experiments and model predictions, there exists an apparent discrepancy in their approach because the utilized theoretical model does not reflect the bifunctional nature of the enzyme system used in experiments. Furthermore, a simple extension of the model to the case of bifunctional enzymes yields predictions that are partially at variance with the experimental results. It seems that an appropriate mechanistic model would have to reconcile two apparent contradictory concepts: ultrasensitivity and bifunctionality.

Li S.,Max Planck Institute for Dynamics of Complex Technical Systems
Journal of chromatography. A | Year: 2010

A new improvement based on outlet fractionation and feedback has been developed for simulated moving bed (SMB) chromatography. In this contribution, this fractionation and feedback SMB (FF-SMB) concept is extended to the general scenario which integrates a simultaneous fractionation of both outlet streams. A model-based optimization approach, previously adopted to investigate single fractionation, is extended to consider this flexible fractionation policy. Quantitative optimization studies based on a specific separation problem reveal that the double fractionation is the most efficient operating scheme in terms of maximum feed throughput, while the two existing single fractionation modes discussed in our previous study are also significantly superior to the conventional SMB operation. The advantages of the double fractionation extension are further demonstrated in terms of several more detailed performance criteria. In order to evaluate the applicability of the fractionation and feedback modification, the effect of product purity, adsorption selectivity, column efficiency and column number on the relative potential of FF-SMB over SMB is examined. 2010 Elsevier B.V. All rights reserved.

Lorenz H.,Max Planck Institute for Dynamics of Complex Technical Systems | Seidel-Morgenstern A.,Otto Von Guericke University of Magdeburg
Angewandte Chemie - International Edition | Year: 2014

The provision of pure enantiomers is of increasing importance not only for the pharmaceutical industry but also for agrochemistry and biotechnology. In general, there are two rival approaches to provide pure enantiomers. The chiral approach is based on developing an asymmetric synthesis of just one of the enantiomers, while the racemic approach is based on separating mixtures of the two enantiomers. In the last few years remarkable progress has been achieved in the latter area. This Review focuses in particular on enantioselective crystallization processes and preparative chromatography, including hybrid processes and the incorporation of racemization steps. Several examples from our research are used for illustration purposes. © 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Straube R.,Max Planck Institute for Dynamics of Complex Technical Systems
Biophysical journal | Year: 2010

We report on the first observation of inward rotating spiral waves (antispirals) in a biochemical reaction-diffusion system. Experiments are performed with extracts from yeast cells in an open spatial reactor. By increasing the protein concentration of the extract we observe a transition from outward to inward propagating waves of glycolytic activity. Numerical simulations with an allosteric model for the phosphofructokinase can reproduce these inward propagating waves over a wide range of parameters if the octameric structure of yeast phosphofructokinase is taken into account. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

von Kamp A.,Max Planck Institute for Dynamics of Complex Technical Systems | Klamt S.,Max Planck Institute for Dynamics of Complex Technical Systems
PLoS Computational Biology | Year: 2014

One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal) provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs) which itself is impractical in genome-scale networks.We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions) in genome-scale metabolic network models. For this we combine two approaches, namely (i) the mapping of MCSs to EMs in a dual network, and (ii) a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine) by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth) than reported previously. The strength of the presented approach is that smallest intervention strategies can be quickly calculated and screened with neither network size nor the number of required interventions posing major challenges. © 2014 von Kamp, Klamt.

Straube R.,Max Planck Institute for Dynamics of Complex Technical Systems
PLoS Computational Biology | Year: 2014

Two-component signal transduction systems, where the phosphorylation state of a regulator protein is modulated by a sensor kinase, are common in bacteria and other microbes. In many of these systems, the sensor kinase is bifunctional catalyzing both, the phosphorylation and the dephosphorylation of the regulator protein in response to input signals. Previous studies have shown that systems with a bifunctional enzyme can adjust the phosphorylation level of the regulator protein independently of the total protein concentrations - a property known as concentration robustness. Here, I argue that two-component systems with a bifunctional enzyme may also exhibit ultrasensitivity if the input signal reciprocally affects multiple activities of the sensor kinase. To this end, I consider the case where an allosteric effector inhibits autophosphorylation and, concomitantly, activates the enzyme's phosphatase activity, as observed experimentally in the PhoQ/PhoP and NRII/NRI systems. A theoretical analysis reveals two operating regimes under steady state conditions depending on the effector affinity: If the affinity is low the system produces a graded response with respect to input signals and exhibits stimulus-dependent concentration robustness - consistent with previous experiments. In contrast, a high-affinity effector may generate ultrasensitivity by a similar mechanism as phosphorylation-dephosphorylation cycles with distinct converter enzymes. The occurrence of ultrasensitivity requires saturation of the sensor kinase's phosphatase activity, but is restricted to low effector concentrations, which suggests that this mode of operation might be employed for the detection and amplification of low abundant input signals. Interestingly, the same mechanism also applies to covalent modification cycles with a bifunctional converter enzyme, which suggests that reciprocal regulation, as a mechanism to generate ultrasensitivity, is not restricted to two-component systems, but may apply more generally to bifunctional enzyme systems. © 2014 Ronny Straube.

Straube R.,Max Planck Institute for Dynamics of Complex Technical Systems
Biophysical Journal | Year: 2013

Regulation by covalent modification is a common mechanism to transmit signals in biological systems. The modifying reactions are catalyzed either by two distinct converter enzymes or by a single bifunctional enzyme (which may employ either one or two catalytic sites for its opposing activities). The reason for this diversification is unclear, but contemporary theoretical models predict that systems with distinct converter enzymes can exhibit enhanced sensitivity to input signals whereas bifunctional enzymes with two catalytic sites are believed to generate robustness against variations in system's components. However, experiments indicate that bifunctional enzymes can also exhibit enhanced sensitivity due to the zero-order effect, raising the question whether both phenomena could be understood within a common mechanistic model. Here, I argue that this is, indeed, the case. Specifically, I show that bifunctional enzymes with two catalytic sites can exhibit both ultrasensitivity and concentration robustness, depending on the kinetic operating regime of the enzyme's opposing activities. The model predictions are discussed in the context of experimental observations of ultrasensitivity and concentration robustness in the uridylylation cycle of the PII protein, and in the phosphorylation cycle of the isocitrate dehydrogenase, respectively. © 2013 Biophysical Society.

Samaga R.,Max Planck Institute for Dynamics of Complex Technical Systems | Klamt S.,Max Planck Institute for Dynamics of Complex Technical Systems
Cell Communication and Signaling | Year: 2013

A central goal of systems biology is the construction of predictive models of bio-molecular networks. Cellular networks of moderate size have been modeled successfully in a quantitative way based on differential equations. However, in large-scale networks, knowledge of mechanistic details and kinetic parameters is often too limited to allow for the set-up of predictive quantitative models.Here, we review methodologies for qualitative and semi-quantitative modeling of cellular signal transduction networks. In particular, we focus on three different but related formalisms facilitating modeling of signaling processes with different levels of detail: interaction graphs, logical/Boolean networks, and logic-based ordinary differential equations (ODEs). Albeit the simplest models possible, interaction graphs allow the identification of important network properties such as signaling paths, feedback loops, or global interdependencies. Logical or Boolean models can be derived from interaction graphs by constraining the logical combination of edges. Logical models can be used to study the basic input-output behavior of the system under investigation and to analyze its qualitative dynamic properties by discrete simulations. They also provide a suitable framework to identify proper intervention strategies enforcing or repressing certain behaviors. Finally, as a third formalism, Boolean networks can be transformed into logic-based ODEs enabling studies on essential quantitative and dynamic features of a signaling network, where time and states are continuous.We describe and illustrate key methods and applications of the different modeling formalisms and discuss their relationships. In particular, as one important aspect for model reuse, we will show how these three modeling approaches can be combined to a modeling pipeline (or model hierarchy) allowing one to start with the simplest representation of a signaling network (interaction graph), which can later be refined to logical and eventually to logic-based ODE models. Importantly, systems and network properties determined in the rougher representation are conserved during these transformations. © 2013 Samaga and Klamt; licensee BioMed Central Ltd.

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