3 papers
q-bio.MN2026
Enforcing Thermodynamic Consistency in Parameter Optimization and Bayesian Inference of Biochemical Reaction Networks
Federica Milinanni, Andrei Kramer-Miehe, Jan Glaubitz +1
Subcellular signaling pathways regulating, e.g., cell division or synaptic plasticity, are often modeled as dynamical networks of reactions satisfying the law of mass action. To re…
q-bio.QM2023
UQSA -- An R-Package for Uncertainty Quantification and Sensitivity Analysis for Biochemical Reaction Network Models
Andrei Kramer, Federica Milinanni, Jeanette Hellgren Kotaleski +3
Biochemical reaction models describing subcellular processes generally come with a large uncertainty. To be able to account for this during the modeling process, we have developed…
math.NA2021
Sensitivity Approximation by the Peano-Baker Series
Olivia Eriksson, Andrei Kramer, Federica Milinanni +1
In this paper we develop a new method for numerically approximating sensitivities in parameter-dependent ordinary differential equations (ODEs). Our approach, intended for situatio…