Special Issue — Selected Papers from GIW 2016; Guest Editors: S. Zhou, P. Y.-P. Chen and H. Mamitsuka: Regular Papers: Research PapersNo Access

Reverse engineering of gene regulatory network using restricted gene expression programming

Bin Yang

School of Information Science and Engineering, Zaozhuang University, Zaozhuang 277160, China

E-mail Address: [email protected]

Corresponding author.

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Sanrong Liu

School of Information Science and Engineering, Zaozhuang University, Zaozhuang 277160, China

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, and

Wei Zhang

School of Information Science and Engineering, Zaozhuang University, Zaozhuang 277160, China

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https://doi.org/10.1142/S0219720016500219Cited by:6 (Source: Crossref)

Abstract

Inference of gene regulatory networks has been becoming a major area of interest in the field of systems biology over the past decade. In this paper, we present a novel representation of S-system model, named restricted gene expression programming (RGEP), to infer gene regulatory network. A new hybrid evolutionary algorithm based on structure-based evolutionary algorithm and cuckoo search (CS) is proposed to optimize the architecture and corresponding parameters of model, respectively. Two synthetic benchmark datasets and one real biological dataset from SOS DNA repair network in E. coli are used to test the validity of our method. Experimental results demonstrate that our proposed method performs better than previously proposed popular methods.

Keywords:

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