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A novel biclustering of gene expression data based on hybrid BAFS-BSA algorithm

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Abstract

As one of usual concepts, co-expressed genes can represent co-regulated genes in gene expression data. This strategy can be refined further because co-expression of the genome may be the result of independent activation under same experimental samples, rather than the same regulatory regime. Therefore, traditional clustering techniques are proposed to find significant clusters, especially, the biclustering technology. By combining Binary Artificial Fish Swarm (BAFS) with Binary Simulated Annealing (BSA) algorithms, the hybrid algorithm named BAFS-BSA-BIC was proposed in this paper. When this method of biclustering was applied to several datasets, lots of biological significant bifclusters were searched, and the results demonstrate the promising clustering performance of our method. The proposed technology was also compared to classical biclustering technologies-CC, QUBIC, FLOC and original BAFS algorithm, and its robustness and quality are better than these algorithms in searching optimal biclusters of co-expressed genes.

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Acknowledgements

We acknowledge the financial support from the National Natural Science Foundation of China (61402240,61502245,61772568), and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_0921).

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Authors and Affiliations

  1. National Engineering Reaearch Center of Communication and Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Yan Cui, Rui Zhang, Huacheng Gao, Yuanyuan Lu & Yinqiu Liu

  2. Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China

    Guangwei Gao

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  1. Yan Cui
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  2. Rui Zhang
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  3. Huacheng Gao
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  4. Yuanyuan Lu
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  5. Yinqiu Liu
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  6. Guangwei Gao
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Correspondence to Yan Cui.

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Cui, Y., Zhang, R., Gao, H. et al. A novel biclustering of gene expression data based on hybrid BAFS-BSA algorithm. Multimed Tools Appl 79, 14811–14824 (2020). https://doi.org/10.1007/s11042-019-7656-7

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