Reference : Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/20338
Reconstruction of arbitrary biochemical reaction networks: A compressive sensing approach
English
Pan, Wei mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Yuan, Y. mailto [> >]
Goncalves, Jorge mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Stan, G.-B. mailto [> >]
2012
The proceedings of the 51st IEEE Conference on Decision and Control
IEEE
2334-2339
Yes
978-1-4673-2064-1
51st IEEE Conference on Decision and Control
10-13 December 2012
Maui
Hawaii
[en] 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.
http://hdl.handle.net/10993/20338
10.1109/CDC.2012.6426216

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Limited access
Reconstruction of arbitrary biochemical reaction networks, A compressive sensing approach.pdfPublisher postprint379.49 kBRequest a copy

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.