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Content Provider | IEEE Xplore Digital Library |
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Author | Wei Pan Ye Yuan Goncalves, J. Stan, G. |
Copyright Year | 2012 |
Description | Author affiliation: Centre for Synthetic Biology and Innovation, Imperial College London, United Kingdom (Wei Pan; Ye Yuan; Stan, G.) || Control Group, Department of Engineering, University of Cambridge, United Kingdom (Goncalves, J.) |
Abstract | Reconstruction of biochemical reaction networks (BRN) and genetic regulatory networks (GRN) in particular is a central topic in systems biology which raises crucial theoretical challenges in system identification. Nonlinear Ordinary Differential Equations (ODEs) that involve polynomial and rational functions are typically used to model biochemical reaction networks. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data quite difficult. In this paper, we present a network reconstruction algorithm that can deal with ODE model descriptions containing polynomial and rational functions. Rather than identifying the parameters of linear or nonlinear ODEs characterised by pre-defined equation structures, our methodology allows us to determine the nonlinear ODEs structure together with their associated parameters. To solve the network reconstruction problem, we cast it as a compressive sensing (CS) problem and use sparse Bayesian learning (SBL) algorithms as a computationally efficient and robust way to obtain its solution. |
Starting Page | 2334 |
Ending Page | 2339 |
File Size | 388597 |
Page Count | 6 |
File Format | |
ISBN | 9781467320658 |
ISSN | 07431546 |
e-ISBN | 9781467320665 |
e-ISBN | 9781467320641 |
DOI | 10.1109/CDC.2012.6426216 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-12-10 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Biological system modeling Equations Mathematical model Bayesian methods Vectors Kinetic theory Compressed sensing |
Content Type | Text |
Resource Type | Article |
Subject | Control and Optimization Control and Systems Engineering Modeling and Simulation |
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