activity
20012023
most citedClassical quasi-steady state reduction -- A mathematical characterization

41 citations · 164 across the 26 of their papers we have counts for

collaborators

28 papers

math.DS2023

Rigorous estimates for the quasi-steady state approximation of the Michaelis-Menten reaction mechanism at low enzyme concentrations

Justin Eilertsen, Santiago Schnell, Sebastian Walcher

There is a vast amount of literature concerning the appropriateness of various perturbation parameters for the standard quasi-steady state approximation in the Michaelis-Menten rea…

math.DS2022

Natural parameter conditions for singular perturbations of chemical and biochemical reaction networks

Justin Eilertsen, Santiago Schnell, Sebastian Walcher

We consider reaction networks that admit a singular perturbation reduction in a certain parameter range. The focus of this paper is on deriving "small parameters" (briefly for smal…

physics.chem-ph2021★ 16 cited

On the anti-quasi-steady-state conditions of enzyme kinetics

Justin Eilertsen, Santiago Schnell, Sebastian Walcher

Quasi-steady state reductions for the irreversible Michaelis--Menten reaction mechanism are of interest both from a theoretical and an experimental design perspective. A number of…

math.DS2021★ 1 cited

Critical parameters for singular perturbation reductions of chemical reaction networks

Elisenda Feliu, Sebastian Walcher, Carsten Wiuf

We are concerned with polynomial ordinary differential systems that arise from modelling chemical reaction networks. For such systems, which may be of high dimension and may depend…

math.DS2021★ 1 cited

On the quasi-steady-state approximation in an open Michaelis--Menten reaction mechanism

Justin Eilertsen, Marc R. Roussel, Santiago Schnell +1

The conditions for the validity of the standard quasi-steady-state approximation in the Michaelis--Menten mechanism in a closed reaction vessel have been well studied, but much les…

q-bio.MN2020★ 9 cited

Algorithmic Reduction of Biological Networks With Multiple Time Scales

Niclas Kruff, Christoph Lüders, Ovidiu Radulescu +2

We present a symbolic algorithmic approach that allows to compute invariant manifolds and corresponding reduced systems for differential equations modeling biological networks whic…