Inference of Gene Expression Networks Using Memetic Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InProceedings{Zarnegar09,

• author = "Armita Zarnegar and Peter Vamplew and Andrew Stranieri",
• title = "Inference of Gene Expression Networks Using Memetic Gene Expression Programming",
• booktitle = "Thirty-Second Australasian Computer Science Conference (ACSC 2009)",
• series = "CRPIT",
• volume = "91",
• pages = "17--23",
• year = "2009",
• editor = "Bernard Mans",
• address = "Wellington, New Zealand",
• keywords = "genetic algorithms, genetic programming, gene expression programming, hill climbing, Differential Equations, Gene Networks, Evolutionary Algorithm, Gene expression Profile, Microarray data",
• publisher = "ACS",
• URL = "http://crpit.com/confpapers/CRPITV91Zarnegar.pdf",
• abstract = "In this paper we aim to infer a model of genetic networks from time series data of gene expression profiles by using a new gene expression programming algorithm. Gene expression networks are modeled by differential equations which represent temporal gene expression relations. Gene Expression Programming is a new extension of genetic programming. Here we combine a local search method with gene expression programming to form a hill climbing algorithm in order to find not only the system of differential equations but also fine tune its constant parameters. The effectiveness of the proposed method is justified by comparing its performance with that of conventional genetic programming applied to this problem in previous studies.",
• notes = "School of Information Technology and Mathematical Sciences, University of Ballarat, P.O. Box 663, Ballarat, Victoria, Australia

  ",

}

Genetic Programming entries for Armita Zarnegar Peter Vamplew Andrew Stranieri

Citations