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Efficiency and Effectiveness Metrics in Evolutionary Algorithms and Their Application Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Using Restricted Additive Tree Model for Identifying the Large-Scale Gene Regulatory Networks

Authors : Bin Yang, Wei Zhang

Published in: Intelligent Computing Theories and Methodologies

Publisher: Springer International Publishing

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Abstract

S-system model has been proposed to identify gene regulatory network in the past years. However, due to the computation complexity, this model is only used for reconstruction of small-scale networks. In this paper, the restricted additive tree model (RAT) is proposed to infer the large-scale gene regulatory networks. In the method, restricted additive tree model is used to encode the S-system model, and the hybrid evolution approach is used to optimize the structure and parameters of restricted additive tree. The large-scale gene regulatory network containing 30 genes is used to test the performance of our method. The results reveal that our method could identify the large-scale gene regulatory network correctly.

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previous chapter A New Representation Method of H1N1 Influenza Virus and Its Application
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Metadata
Title
Using Restricted Additive Tree Model for Identifying the Large-Scale Gene Regulatory Networks
Authors
Bin Yang
Wei Zhang
Copyright Year
2015
Book
Intelligent Computing Theories and Methodologies

Print ISBN: 978-3-319-22185-4

Electronic ISBN: 978-3-319-22186-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-22186-1_34

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