Biochemical networks typically exhibit intricate topologies that hinder their analysis with control-theoretic tools. In this work we present a systematic methodology for the identification of the control structure of a reaction network. The method is based on a bandwidth reduction technique applied to the incidence matrix of the network’s graph. In addition, in the case of mass-action and stable networks we show that it is possible to identify linear algebraic dependencies between the time-domain integrals of some species’ concentrations. We consider the extrinsic apoptosis pathway and an activation– inhibition mechanism to illustrate the application of our result
Processing of information by signaling networks is characterized by properties of the induced kineti...
Biochemical reaction networks typically consist of a complicated structure with many interacting spe...
In this thesis we address dynamic systems problems that arise from the study of biochemical network...
Biochemical networks typically exhibit intricate topologies that hinder their analysis with control...
Biochemical networks consist of highly interconnected dynamic systems of chemical reaction represent...
The aim of this thesis is to improve the understanding of signaling pathways through a theoretical s...
In biological cells, chemical reaction pathways lead to complex network systems like metabolic netwo...
Abstract Background With the rapid development of high-throughput experiments, detecting functional ...
A biochemical reaction network is the system in which biochemical species interact through various r...
Background Determining the interaction topology of biological systems is a topic that currently att...
The nonlinearities found in molecular networks usually prevent mathematical analysis of network beha...
International audienceBiochemical networks are used in computational biology, to model the static an...
This monograph addresses the decomposition of biochemical networks into functional modules that pres...
Different types of macroscopic reaction kinetics can be derived from microscopic molecular interacti...
The project aims at a study of the nonlinear systems arising in the biochemical processes occuring i...
Processing of information by signaling networks is characterized by properties of the induced kineti...
Biochemical reaction networks typically consist of a complicated structure with many interacting spe...
In this thesis we address dynamic systems problems that arise from the study of biochemical network...
Biochemical networks typically exhibit intricate topologies that hinder their analysis with control...
Biochemical networks consist of highly interconnected dynamic systems of chemical reaction represent...
The aim of this thesis is to improve the understanding of signaling pathways through a theoretical s...
In biological cells, chemical reaction pathways lead to complex network systems like metabolic netwo...
Abstract Background With the rapid development of high-throughput experiments, detecting functional ...
A biochemical reaction network is the system in which biochemical species interact through various r...
Background Determining the interaction topology of biological systems is a topic that currently att...
The nonlinearities found in molecular networks usually prevent mathematical analysis of network beha...
International audienceBiochemical networks are used in computational biology, to model the static an...
This monograph addresses the decomposition of biochemical networks into functional modules that pres...
Different types of macroscopic reaction kinetics can be derived from microscopic molecular interacti...
The project aims at a study of the nonlinear systems arising in the biochemical processes occuring i...
Processing of information by signaling networks is characterized by properties of the induced kineti...
Biochemical reaction networks typically consist of a complicated structure with many interacting spe...
In this thesis we address dynamic systems problems that arise from the study of biochemical network...