CGP-WPSO Hybrid Algorithm for Gene Regulatory Network Construction

DOI

10.2991/emcs-17.2017.50How to use a DOI?

Keywords

Gene regulatory network; Hybrid algorithm; Particle swarm optimization; Inference of gene network; Optimal strategy

Abstract

It is of great significance for the global food security to rely on the gene regulatory network to predict the performance of crops. A hybrid algorithm based on Cartesian genetic programming and linear decreasing inertia weight particle swarm optimization is proposed. Furthermore, in order to verify the effectiveness of the algorithm, the algorithm is applied to the problem of model reconstruction of Arabidopsis flowering regulatory system. Finally, the simulation results show that the algorithm can be based on crop genotypes and environmental conditions, the reconstruction can accurately predict the gene regulatory network model crop type. And the proposed algorithm can be suitable for gene regulatory network

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ming Zheng
AU  - Mugui Zhuo
PY  - 2017/03
DA  - 2017/03
TI  - CGP-WPSO Hybrid Algorithm for Gene Regulatory Network Construction
BT  - Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
PB  - Atlantis Press
SP  - 253
EP  - 257
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-17.2017.50
DO  - 10.2991/emcs-17.2017.50
ID  - Zheng2017/03
ER  -