Inference of Gene Expression Networks Using Memetic Gene Expression Programming

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 modelled 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 memetic 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.

• Type: Conference
• Year: 2009
• Where: ACSC
• Authors: Armita Zarnegar, Peter Vamplew, Andrew Stranieri
• Keywords: ACSC 2009, Computer Science, Gene Expression, Gene Expression Networks, Gene Expression Programming