NDLI: Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach

Content Provider	IEEE Xplore Digital Library
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	PDF
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 Systems Engineering Modeling and Simulation Control and Optimization

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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