Reference : Inference of switched biochemical reaction networks using sparse bayesian learning
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/10993/20819
Inference of switched biochemical reaction networks using sparse bayesian learning
English
Pan, Wei mailto []
Yuan, Y. []
Sootla, A. []
Stan, G.B []
2014
The proceedings of the 7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)
Springer
p.51-60
Yes
7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)
15-19 September, 2014
Nancy
France
[en] Switched system ; Sparse Bayesian Learning ; Convex-Concave programming
[en] This paper proposes an algorithm to identify biochemical reaction networks with time-varying kinetics. We formulate the problem as a nonconvex optimisation problem casted in a sparse Bayesian learning framework. The nonconvex problem can be efficiently solved using Convex-Concave programming. We test the effectiveness of the method on a simulated example of DNA circuit realising a switched chaotic Lorenz oscillator.
http://hdl.handle.net/10993/20819

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Limited access
Inference of Switched Biochemical Reaction Networks Using Sparse Bayesian Learning.pdfPublisher postprint431.48 kBRequest a copy

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.