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20 Publications visible to you, out of a total of 20
Data2Dynamics: a modeling environment tailored to parameter estimation in dynamical systems.

Abstract (Expand)

UNLABELLED: Modeling of dynamical systems using ordinary differential equations is a popular approach in the field of systems biology. Two of the most critical steps in this approach are to construct … dynamical models of biochemical reaction networks for large datasets and complex experimental conditions and to perform efficient and reliable parameter estimation for model fitting. We present a modeling environment for MATLAB that pioneers these challenges. The numerically expensive parts of the calculations such as the solving of the differential equations and of the associated sensitivity system are parallelized and automatically compiled into efficient C code. A variety of parameter estimation algorithms as well as frequentist and Bayesian methods for uncertainty analysis have been implemented and used on a range of applications that lead to publications. AVAILABILITY AND IMPLEMENTATION: The Data2Dynamics modeling environment is MATLAB based, open source and freely available at http://www.data2dynamics.org. CONTACT: andreas.raue@fdm.uni-freiburg.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: A. Raue, B. Steiert, M. Schelker, C. Kreutz, T. Maiwald, H. Hass, J. Vanlier, C. Tonsing, L. Adlung, R. Engesser, W. Mader, T. Heinemann, J. Hasenauer, M. Schilling, T. Hofer, E. Klipp, F. Theis, U. Klingmuller, B. Schoberl, J. Timmer

Date Published: 1st Nov 2015

Publication Type: Journal

Differences between healthy hematopoietic progenitors and leukemia cells with respect to CD44 mediated rolling versus adherence behavior on hyaluronic acid coated surfaces.

Abstract (Expand)

We previously demonstrated that leukemia cell lines expressing CD44 and hematopoietic progenitor cells (HPC) from umbilical cord blood (CB) showed rolling on hyaluronic acid (HA)-coated surfaces under … physiological shear stress. In the present study, we quantitatively assessed the interaction of HPC derived from CB, mobilized peripheral blood (mPB) and bone marrow (BM) from healthy donors, as well as primary leukemia blasts from PB and BM of patients with acute myeloid leukemia (AML) with HA. We have demonstrated that HPC derived from healthy donors showed relative homogeneous rolling and adhesion to HA. In contrast, highly diverse behavioral patterns were found for leukemia blasts under identical conditions. The monoclonal CD44 antibody (clone BU52) abrogated the shear stress-induced rolling of HPC and leukemia blasts, confirming the significance of CD44 in this context. On the other hand, the immobile adhesion of leukemia blasts to the HA-coated surface was, in some cases, not or incompletely inhibited by BU52. The latter property was associated with non-responsiveness to induction chemotherapy and subsequently poor clinical outcome.

Authors: M. Hanke, I. Hoffmann, C. Christophis, M. Schubert, V. T. Hoang, A. Zepeda-Moreno, N. Baran, V. Eckstein, P. Wuchter, A. Rosenhahn, A. D. Ho

Date Published: 26th Nov 2013

Publication Type: Journal

Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling.

Abstract (Expand)

Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations … is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) and mitogen activated protein kinase (MAPK) signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks.

Authors: L. A. D'Alessandro, R. Samaga, T. Maiwald, S. H. Rho, S. Bonefas, A. Raue, N. Iwamoto, A. Kienast, K. Waldow, R. Meyer, M. Schilling, J. Timmer, S. Klamt, U. Klingmuller

Date Published: 24th Apr 2015

Publication Type: Journal

Driving the Model to Its Limit: Profile Likelihood Based Model Reduction

Abstract (Expand)

In systems biology, one of the major tasks is to tailor model complexity to information content of the data. A useful model should describe the data and produce well-determined parameter estimates and … predictions. Too small of a model will not be able to describe the data whereas a model which is too large tends to overfit measurement errors and does not provide precise predictions. Typically, the model is modified and tuned to fit the data, which often results in an oversized model. To restore the balance between model complexity and available measurements, either new data has to be gathered or the model has to be reduced. In this manuscript, we present a data-based method for reducing non-linear models. The profile likelihood is utilised to assess parameter identifiability and designate likely candidates for reduction. Parameter dependencies are analysed along profiles, providing context-dependent suggestions for the type of reduction. We discriminate four distinct scenarios, each associated with a specific model reduction strategy. Iterating the presented procedure eventually results in an identifiable model, which is capable of generating precise and testable predictions. Source code for all toy examples is provided within the freely available, open-source modelling environment Data2Dynamics based on MATLAB available at http://www.data2dynamics.org/, as well as the R packages dMod/cOde available at https://github.com/dkaschek/. Moreover, the concept is generally applicable and can readily be used with any software capable of calculating the profile likelihood.

Authors: T. Maiwald, H. Hass, B. Steiert, J. Vanlier, R. Engesser, A. Raue, F. Kipkeew, H. H. Bock, D. Kaschek, C. Kreutz, J. Timmer

Date Published: 3rd Sep 2016

Publication Type: Not specified

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