Ordinary differential equation models are nowadays widely used for the mechanistic
description of biological processes and their temporal evolution. These models typically …

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 parameter …

Mechanistic models are important tools to describe and understand biological processes.
However, they typically rely on unknown parameters, the estimation of which can be …

Kinetic modeling of in vitro enzymatic reaction networks is vital to understand and control the
complex behaviors emerging from the nonlinear interactions inside. However, modeling is …

Motivation Unknown parameters of dynamical models are commonly estimated from
experimental data. However, while various efficient optimization and uncertainty analysis …

Mathematical models are often used to explore network-driven cellular processes from a
systems perspective. However, a dearth of quantitative data suitable for model calibration …

Results Overview of the nucleotide salvage pathway The in vitro ERN constructed in this
work derives from the nucleotide salvage pathway (Fig. 1 a), which regenerates nucleotides …

Quantitative dynamical models facilitate the understanding of biological processes and the
prediction of their dynamics. The parameters of these models are commonly estimated from …

Modeling biological processes is a highly demanding task because not all processes are
fully understood. Mathematical models allow us to test hypotheses about possible …

Continuous time Markov chains are a common mathematical model for a range of natural
and computer systems. An important part of constructing such models is fitting the model …