吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (5): 1429-1434.doi: 10.7964/jdxbgxb201405033

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Novel method for microarray data dimension reduction

WANG Gang1,2,3, ZHANG Yu-xuan4, LI Ying1,2, CHEN Hui-ling5, HU Wei-tong6, QIN Lei1,2   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
    2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China;
    3.College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    4.College of Communication Engineering, Jilin University, Changchun 130012, China;
    5.College of Physics and Electronic Information, Wenzhou University, Wenzhou 325035, China;
    6.Basic Course Department, Air Force Aviation University, Changchun 130022, China
  • Received:2013-07-05 Online:2014-09-01 Published:2014-09-01

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Abstract: A two stage parallel gene selection method (TPM) for obtaining the optimal feature subset is proposed. A fuzzy multi-swarm particle optimization (FMP) is also proposed to extend the searching spaces, to overcome the problem of traditional algorithm to be locked to local optimum. The performance of the TMP is evaluated on five microarray datasets (leukemia dataset, colon dataset, breast cancer dataset, lung carcinoma dataset and brain cancer dataset). The comparison results show that the proposed method not only gets better quality of feature subset and higher classification accuracy, but also generates smaller feature subsets. The results of this study could provide a new idea to the field of gene expression.

Key words: computer application, gene selection, feature selection, microarray, particle swarm optimization

CLC Number: 

  • TP301.6
[1] 刘元宁,王刚, 赵正东, 等. 基于自适应多种群遗传算法的特征选择[J].吉林大学学报:工学版, 2011, 41(6): 1690-1693.Liu Yuan-ning, Wang Gang, Zhao Zheng-dong, et al. Feature selection based on adaptive multi-population genetic algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2011, 41(6): 1690-1693.
[2] Liu Y, Wang G, Chen H. An improved particle swarm optimization for feature selection[J].Journal of Bionic Engineering, 2011, 8(2): 191-200.
[3] Wang G, Zhang W, Ning Q, et al. A novel framework based on ACO and PSO for RNA secondary structure prediction[J]. Mathematical Problems in Engineering, 2013, 3(2): 1024-1031.
[4] Yildiz Q, Tez M, Bilge H S, et al. Gene selection for breast cancer classification based on data fusion and genetic algorithm[J].Journal of the Faculty of Engineering and Architecture of Gazi University, 2012,27(3):659-668.
[5] Mohamad M S, Omatu S, Deris S, et al. A modified binary particle swarm optimization for selecting the small subset of informative genes from gene expression data[J].IEEE Transactions on Information Technology in Biomedicine, 2011, 15(6):813-822.
[6] Chuang L Y, Yang C H, Li J C. A hybrid BPSO-CGA approach for gene selection and classification of microarray data[J]. Journal of Computational Biology,2012,19(1): 68-82.
[7] Garcia-Nieto J, Alba E. Parallel multi-swarm optimizer for gene selection in DNA microarrays[J].Applied Intelligence,2012,37(2):255-266.
[8] Abdi M J, Hosseini S M, Rezghi M. A novel weighted support vector machine based on particle swarm optimization for gene selection and tumor classification[J].Computational and Mathematical Methods in Medicine,2012, 12(5): 78-85.
[9] Kabir M M, Shahjahan M, Murase K. A new hybrid ant colony optimization algorithm for feature selection[J]. Expert Systems with Applications, 2012,39(3):3747-3763.
[10] Li Y, Wang G. An ant colony optimization based dimension reduction method for high-dimensional datasets[J]. Journal of Bionic Engineering, 2013, 10(2):231-241.
[11] 王刚, 刘元宁, 陈慧灵, 等. 粗糙集与支持向量机在肝炎诊断中的应用[J].吉林大学学报:工学版, 2011, 41(1):160-164.Wang Gang, Liu Yuan-ning, Chen Hui-ling, et al. Application of rough set and support vector machines in hepatitis diagnosis[J]. Journal of Jilin University(Engineering and Technology Edition), 2011, 41(1):160-164.
[12] 王刚, 刘元宁, 张晓旭, 等. 基于模糊自适应粒子群的垃圾邮件过滤方法[J].吉林大学学报:工学版, 2011, 41 (3): 716-720. Wang Gang, Liu Yuan-ning, Zhang Xiao-xu, et al. Novel spam filtering method based on fuzzy adaptive particle swarm optimization[J]. Journal of Jilin University(Engineering and Technology Edition), 2011, 41 (3): 716-720.
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