peer reviewedThis paper addresses the problem of model reduction for dynamical system models that describe biochemical reaction networks. Inherent in such models are properties such as stability, positivity and network structure. Ideally these properties should be preserved by model reduction procedures, although traditional projection based approaches struggle to do this. We propose a projection based model reduction algorithm which uses generalised block diagonal Gramians to preserve structure and positivity. Two algorithms are presented, one provides more accurate reduced order models, the second provides easier to simulate reduced order models
The chemical master equation (CME) is well known to provide the highest resolution models of a bioch...
Many complex kinetic models in the field of biochemical reactions contain a large number of species ...
peer reviewedReconstructed models of biochemical networks often reflect the high level of complexity...
peer reviewedThis paper addresses the problem of model reduction for dynamical system models that de...
peer reviewedIn this paper, we consider the problem of model order reduction of stochastic biochemic...
Abstract — In this paper, we consider the problem of model order reduction of stochastic biochemical...
Abstract — In this paper, we consider the problem of model order reduction of stochastic biochemical...
International audienceBiochemical networks are used in computational biology, to model the static an...
International audienceBiochemical networks are used in computational biology, to model the static an...
Biochemical networks are used in computational biology, to model the static and dynamical details of...
Abstract — Reconstructed models of biochemical networks of-ten reflect the high level of complexity ...
peer reviewedReconstructed models of biochemical networks often reflect the high level of complexity...
The chemical master equation (CME) is well known to provide the highest resolution models of a bioch...
Reconstructed models of biochemical networks often reflect the high level of complexity inherent in ...
The chemical master equation (CME) is well known to provide the highest resolution models of a bioch...
The chemical master equation (CME) is well known to provide the highest resolution models of a bioch...
Many complex kinetic models in the field of biochemical reactions contain a large number of species ...
peer reviewedReconstructed models of biochemical networks often reflect the high level of complexity...
peer reviewedThis paper addresses the problem of model reduction for dynamical system models that de...
peer reviewedIn this paper, we consider the problem of model order reduction of stochastic biochemic...
Abstract — In this paper, we consider the problem of model order reduction of stochastic biochemical...
Abstract — In this paper, we consider the problem of model order reduction of stochastic biochemical...
International audienceBiochemical networks are used in computational biology, to model the static an...
International audienceBiochemical networks are used in computational biology, to model the static an...
Biochemical networks are used in computational biology, to model the static and dynamical details of...
Abstract — Reconstructed models of biochemical networks of-ten reflect the high level of complexity ...
peer reviewedReconstructed models of biochemical networks often reflect the high level of complexity...
The chemical master equation (CME) is well known to provide the highest resolution models of a bioch...
Reconstructed models of biochemical networks often reflect the high level of complexity inherent in ...
The chemical master equation (CME) is well known to provide the highest resolution models of a bioch...
The chemical master equation (CME) is well known to provide the highest resolution models of a bioch...
Many complex kinetic models in the field of biochemical reactions contain a large number of species ...
peer reviewedReconstructed models of biochemical networks often reflect the high level of complexity...