Comparing Genetic Programming and Evolution Strategies on Inferring Gene Regulatory Networks

In recent years several strategies for inferring gene regulatory networks from observed time series data of gene expression have been suggested based on Evolutionary Algorithms. But often only few problem instances are investigated and the proposed strategies are rarely compared to alternative strategies. In this paper we compare Evolution Strategies and Genetic Programming with respect to their performance on multiple problem instances with varying parameters. We show that single problem instances are not sufficient to prove the effectiveness of a given strategy and that the Genetic Programming approach is less prone to varying instances than the Evolution Strategy.

[1]  Isao Ono,et al.  Finding multiple solutions based on an evolutionary algorithm for inference of genetic networks by S-system , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[2]  Gary D. Stormo,et al.  Modeling Regulatory Networks with Weight Matrices , 1998, Pacific Symposium on Biocomputing.

[3]  Ting Chen,et al.  Modeling Gene Expression with Differential Equations , 1998, Pacific Symposium on Biocomputing.

[4]  John R. Koza,et al.  Genetic Programming III: Darwinian Invention & Problem Solving , 1999 .

[5]  H. Iba,et al.  Inferring a system of differential equations for a gene regulatory network by using genetic programming , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[6]  Satoru Miyano,et al.  Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function , 2000, RECOMB '00.

[7]  Pedro Mendes,et al.  Artificial gene networks for objective comparison of analysis algorithms , 2003, ECCB.

[8]  Andreas Zell,et al.  Iteratively Inferring Gene Regulatory Networks with Virtual Knockout Experiments , 2004, EvoWorkshops.

[9]  M Wahde,et al.  Coarse-grained reverse engineering of genetic regulatory networks. , 2000, Bio Systems.

[10]  D Thieffry,et al.  Qualitative analysis of gene networks. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[11]  Satoru Miyano,et al.  Identification of Genetic Networks from a Small Number of Gene Expression Patterns Under the Boolean Network Model , 1998, Pacific Symposium on Biocomputing.

[12]  Masahiro Okamoto,et al.  Nonlinear Numerical Optimization Technique Based on a Genetic Algorithm for Inverse Problems: Towards the Inference of Genetic Networks , 1999, German Conference on Bioinformatics.

[13]  A Wuensche,et al.  Genomic regulation modeled as a network with basins of attraction. , 1998, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[14]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[15]  Nikolaus Hansen,et al.  Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaptation , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.