An increasing number of industrial bioprocesses capitalize on living cells by using them as
cell factories that convert sugars into chemicals. These processes range from the production …

Complex models of biochemical reaction systems have become increasingly common in the
systems biology literature. The complexity of such models can present a number of …

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 …

Dynamic models of biochemical networks are often formulated as sets of non-linear ordinary
differential equations, whose states are the concentrations or abundances of the network …

The paper has two goals:(1) It presents basic ideas, notions, and methods for reduction of
reaction kinetics models: quasi-steady-state, quasi-equilibrium, slow invariant manifolds …

Ordinary differential equations (ODEs) with polynomial derivatives are a fundamental tool for
understanding the dynamics of systems across many branches of science, but our ability to …

Background In this paper we propose a model reduction method for biochemical reaction
networks governed by a variety of reversible and irreversible enzyme kinetic rate laws …

It is often predicted that model‐based data analysis will revolutionize biology, just as it has
physics and engineering. A widely used tool within such analysis is hypothesis testing …

Motivation Gene–environment interaction (GEI) studies are a general framework that can be
used to identify genetic variants that modify the effects of environmental, physiological …

In this paper we derive a compact mathematical formulation describing the dynamics of
chemical reaction networks that are complex-balanced and are governed by mass action …