Felix Streichert, Hannes Planatscher, Christian Spieth, Holger Ulmer, and Andreas Zell

Comparing Genetic Programming and Evolution Strategies on Inferring Gene Regulatory Networks

Published at the Genetic and Evolutionary Computation Conference - GECCO 2004 in Seattle, Washington

Abstract

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.

Download

[pdf], [ps]

BibTeX 

@inproceedings{Streichert04Comparing,
  author 	= {Felix Streichert and Hannes Planatscher and Christian Spieth and Holger Ulmer and Andreas Zell},
  title 	= {Comparing Genetic Programming and Evolution Strategies on Inferring Gene Regulatory Networks },
  booktitle 	= {Genetic and Evolutionary Computation Conference - {GECCO 2004}},  
  year 		= {2004},
  month 	= {June 26-30},
  editor    	= {Kalyanmoy Deb and Riccardo Poli and Wolfgang Banzhaf and Hans-Georg Beyer and Edmund K. Burke and Paul J. Darwen and Dipankar Dasgupta and Dario Floreano and James A. Foster and Mark Harman and Owen Holland and Pier Luca Lanzi and Lee Spector and Andrea Tettamanzi and Dirk Thierens and Andrew M. Tyrrell},    
  series 	= {LNCS},
  volume 	= {3102},
  address 	= {Seattle, Washington, USA},
  publisher 	= {Springer Verlag},
  publisher_address = {Berlin},
  pages 	= {471-480},
  ISBN 		= {3-540-22344-4},
  url		= "http://www.ra.cs.uni-tuebingen.de/mitarb/streiche/welcome_e.html"
}