Inference of Chemical Reaction Networks Using Hybrid S-system Models
-
Dominic P Searson
This article demonstrates, using simulations, the potential of the S-system formalism for the inference of unknown chemical reaction networks from simple experimental data, such as that typically obtained from laboratory scale reaction vessels. Virtually no prior knowledge of the products and reactants is assumed. S-systems are a power law formalism for the canonical approximate representation of dynamic non-linear systems. This formalism has the useful property that the structure of a network is dictated only by the values of the power law parameters. This means that network inference problems (e.g. inference of the topology of a chemical reaction network) can be recast as parameter estimation problems. The use of S-systems for network inference from data has been reported in a number of biological fields, including metabolic pathway analysis and the inference of gene regulatory networks. Here, the methodology is adapted for use as a hybrid modelling tool to facilitate the reverse engineering of chemical reaction networks using time series concentration data from fed-batch reactor experiments. The principle of the approach is demonstrated with noisy simulated data from fed-batch reactor experiments using a hypothetical reaction network comprising 5 chemical species involved in 4 parallel reactions. A co-evolutionary algorithm is employed to evolve the structure and the parameter values of the S-system equations concurrently. The S-system equations are then interpreted in order to construct a network diagram that accurately reflects the underlying chemical reaction network.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Artikel in diesem Heft
- Review
- A Generalized Kinetic Model for Hydrometallurgical Processes
- Advanced Modeling of Reactive Separation Units with Structured Packings
- Applications of Computational Fluid Dynamics (CFD) Tools for Gravity Concentrators in Coal Preparation
- Article
- CFD Diagnosis of the Cyclotol Manufacturing Plant: Product Quality and Process Operation
- Performance Analysis of Three Controllers for the Polymerisation of Styrene in a Batch Reactor
- Enhanced Explicit Scheme to Solve Transient Heat Conduction Problem
- Analysis and Simulation of Cross-Flow Reactor for Ethylene Epoxidation
- Learning to Control pH Processes at Multiple Time Scales: Performance Assessment in a Laboratory Plant
- Estimating Output Variance in Closed Loop Systems
- CFD Simulations for Continuous Flow of Bubbles through Gas-Liquid Columns: Application of VOF Method
- Inference of Chemical Reaction Networks Using Hybrid S-system Models
- Optimization of the Variable Reflux Ratio in a Batch Distillation Column through a Heuristic Method
- Spatial and Temporal Resolution in Data-Driven Process Modeling of an Integrated Newsprint Mill
Artikel in diesem Heft
- Review
- A Generalized Kinetic Model for Hydrometallurgical Processes
- Advanced Modeling of Reactive Separation Units with Structured Packings
- Applications of Computational Fluid Dynamics (CFD) Tools for Gravity Concentrators in Coal Preparation
- Article
- CFD Diagnosis of the Cyclotol Manufacturing Plant: Product Quality and Process Operation
- Performance Analysis of Three Controllers for the Polymerisation of Styrene in a Batch Reactor
- Enhanced Explicit Scheme to Solve Transient Heat Conduction Problem
- Analysis and Simulation of Cross-Flow Reactor for Ethylene Epoxidation
- Learning to Control pH Processes at Multiple Time Scales: Performance Assessment in a Laboratory Plant
- Estimating Output Variance in Closed Loop Systems
- CFD Simulations for Continuous Flow of Bubbles through Gas-Liquid Columns: Application of VOF Method
- Inference of Chemical Reaction Networks Using Hybrid S-system Models
- Optimization of the Variable Reflux Ratio in a Batch Distillation Column through a Heuristic Method
- Spatial and Temporal Resolution in Data-Driven Process Modeling of an Integrated Newsprint Mill
