130 citations · 397 across the 8 of their papers we have counts for
9 papers
Constructing Exact Confidence Regions on Parameter Manifolds of Non-Linear Models
Rafael Arutjunjan, Bjoern Malte Schaefer, Clemens Kreutz
Using the mathematical framework of information geometry, we introduce a novel method which allows one to efficiently determine the exact shape of simultaneous confidence regions f…
Rcall: Calling R from Matlab
Janine Egert, Clemens Kreutz
Summary: R and Matlab are two high-level scientific programming languages which are frequently applied in computational biology. To extend the wide variety of available and approve…
Using Differentiable Programming for Flexible Statistical Modeling
Maren Hackenberg, Marlon Grodd, Clemens Kreutz +5
Differentiable programming has recently received much interest as a paradigm that facilitates taking gradients of computer programs. While the corresponding flexible gradient-based…
PEtab -- interoperable specification of parameter estimation problems in systems biology
Leonard Schmiester, Yannik Schälte, Frank T. Bergmann +26
Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been -- so far -- no broadly supported format for the specification of p…
Guidelines for benchmarking of optimization approaches for fitting mathematical models
Clemens Kreutz
Insufficient performance of optimization approaches for fitting of mathematical models is still a major bottleneck in systems biology. In this manuscript, the reasons and methodolo…
An easy and efficient approach for testing identifiability of parameters
Clemens Kreutz
The feasibility of uniquely estimating parameters of dynamical systems from observations is a widely discussed aspect of mathematical modelling. Several approaches have been publis…
Cause and Cure of Sloppiness in Ordinary Differential Equation Models
Christian Tönsing, Jens Timmer, Clemens Kreutz
Data-based mathematical modeling of biochemical reaction networks, e.g. by nonlinear ordinary differential equation (ODE) models, has been successfully applied. In this context, pa…
Joining Forces of Bayesian and Frequentist Methodology: A Study for Inference in the Presence of Non-Identifiability
Andreas Raue, Clemens Kreutz, Fabian Joachim Theis +1
Increasingly complex applications involve large datasets in combination with non-linear and high dimensional mathematical models. In this context, statistical inference is a challe…
Likelihood based observability analysis and confidence intervals for predictions of dynamic models
Clemens Kreutz, Andreas Raue, Jens Timmer
Mechanistic dynamic models of biochemical networks such as Ordinary Differential Equations (ODEs) contain unknown parameters like the reaction rate constants and the initial concen…