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Inference of switched biochemical reaction networks using sparse bayesian learning
Pan, Wei; Yuan, Y.; Sootla, A. et al.
2014In The proceedings of the 7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)
Peer reviewed
 

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Keywords :
Switched system; Sparse Bayesian Learning; Convex-Concave programming
Abstract :
[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.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Pan, Wei 
Yuan, Y.
Sootla, A.
Stan, G.B
External co-authors :
yes
Language :
English
Title :
Inference of switched biochemical reaction networks using sparse bayesian learning
Publication date :
2014
Event name :
7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)
Event place :
Nancy, France
Event date :
15-19 September, 2014
Main work title :
The proceedings of the 7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)
Publisher :
Springer
Pages :
p.51-60
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 15 April 2015

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