Abstract
Gene regulatory networks have been studied in the past few years and it is still a hot topic. This paper presents a different evolutionary method for inferring gene regulatory networks (GRNs) using a system of ordinary differential equations (ODEs) as a network model based on time-series microarray data. An evolutionary algorithm based on the additive tree-structure model is applied to identify the structure of the model and genetic algorithm (GA) is used to optimize the parameters of the ODEs. The experimental results show that the proposed method is feasible and effective for inferring gene regulatory networks.
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© 2014 Springer International Publishing Switzerland
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Li, G., Chen, Y., Yang, B., Zhao, Y., Wang, D. (2014). Evolving Additive Tree Model for Inferring Gene Regulatory Networks. In: Huang, DS., Han, K., Gromiha, M. (eds) Intelligent Computing in Bioinformatics. ICIC 2014. Lecture Notes in Computer Science(), vol 8590. Springer, Cham. https://doi.org/10.1007/978-3-319-09330-7_18
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DOI: https://doi.org/10.1007/978-3-319-09330-7_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09329-1
Online ISBN: 978-3-319-09330-7
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