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Articles

A New Hybrid Cuckoo Search Algorithm for Biclustering of Microarray Gene-Expression Data

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References

  • Angiulli, F., E. Cesario, and C. Pizzuti. 2008. Random walk biclustering for microarray data. Information Science 178 (6):1479–97. doi:10.1016/j.ins.2007.11.007.
  • Ayadi, W., M. Elloumi, and J. Hao. 2009. A biclustering algorithm based on a bicluster enumeration tree: Application to DNA microarray data. BioData Mining 2:1–9. doi:10.1186/1756-0381-2-1.
  • Ayadi, W., M. Elloumi, and J. Hao. 2012a. Pattern-driven neighborhood search for biclustering microarray data. BMC Bioinformatics 7:452–66.
  • Ayadi, W., M. Elloumi, and J. Hao. 2012b. BicFinder: A biclustering algorithm for microarray data analysis. Knowledge Information System 30:341–58. doi:10.1007/s10115-011-0383-7.
  • Ayadi, W., M. Elloumi, and J. Hao. 2014. A memetic algorithm for discovering negative correlation biclusters of DNA microarray data. Neurocomputing 145:14–22. doi:10.1016/j.neucom.2014.05.074.
  • Ben-Dor, A., B. Chor, R. Karp, and Z. Yakhini. 2003. Discovering local structure in gene expression data: The order-preserving submatrix problem. Journal of Computational Biology 10:373–84. doi:10.1089/10665270360688075.
  • Bergmann, S., J. Ihmels, and N. Barkai. 2003. Iterative signature algorithm for the analysis of large-scale gene expression data. Physical Review E 67:1–18. doi:10.1103/PhysRevE.67.031902.
  • Berriz, G. F., O. D. King, B. Bryant, C. Sander, and P. Frederick. 2003. Charactering gene sets with FuncAssociate’. BMC Bioinformatics 19:2502–04. doi:10.1093/bioinformatics/btg363.
  • Bleuler, S., A. Prelic, and E. Zitzler. 2014. An EA framework for biclustering of gene expression data. Proceeding Congress of IEEE on Evolutionary Computation 32:166–73.
  • Blum, C., and A. Roli. 2003. Metaheuristics in combinatorial optimization: overview and conceptual comparison. Journal Acm Computing Surveys 35 (3):268–308. doi:10.1145/937503.
  • Cheng, Y., and G. M. Church. 2000. Biclustering of expression data’. Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, Menlo Park, United States, 93–103.
  • Cho, R. J., M. J. Campbell, E. A. Winzeler, L. Steinmetz, A. Conway, L. Wodicka, T. G. Wolfsberg, A. E. Gabrielian, D. Landsman, and D. J. Lockhart. 1998. A genome-wide transcriptional analysis of the mitotic cell cycle’. Molecular Cell 2:65–73.
  • Christian, B., and Andrea, R. 2003. Metaheuristics in combinatorial optimization: Overview and conceptual comparison. Journal ACM Computing Surveys. 35 (3):268–308.
  • Divina, F., and J. S. Aguilar-Ruiz. 2006. Biclustering of expression data with evolutionary computation. IEEE Transactions on Knowledge Data Engineering 18:590–602. doi:10.1109/TKDE.2006.74.
  • Eusuff, M. M., K. Lansey, and F. Pasha. 2006. Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization. Engineering Optimization 38:129–54. doi:10.1080/03052150500384759.
  • Gasch, A. P., P. T. Spellman, C. M. Kao, O. Carmel-Harel, M. B. Eisen, G. Storz, D. Botstein, and P. O. Brown. 2000. Genomic expression programs in the response of yeast cells to environmental changes. Molecular Biology of the Cell 11:4241–57. doi:10.1091/mbc.11.12.4241.
  • Julio, R., and Michael, W. 1997. An optimization-based econometric framework for the evaluation of monetary policy. NBER Macroeconomics Annual 1997, 12:297–361.
  • Kennedy, J., and R. C. Eberhart. 1997. A discrete binary version of the particle swarm Algorithm, IEEE international Conference on Systems, Man and Cybernetics, Washington, United States, 5, 4104–8.
  • Liu, J., Z. Li, X. Hu, and Y. Chen. 2009. Biclustering of microarray data with mospo based on crowding distance. Bioinformatics 10:1–12.
  • Liu, X., and L. Wang. 2007. Computing the maximum similarity bi-clusters of gene expression data. BMC Bioinformatics 23:50–56. doi:10.1093/bioinformatics/btl560.
  • Lockhart, D. J., and E. A. Winzeler. 2000. Genomics, gene expression and DNA arrays. Nature 405:827–36. doi:10.1038/35015701.
  • Maatouk, O., W. Ayadi, H. Bouziri, and B. Duval. 2014. Evolutionary algorithm based on new crossover for the biclustering of gene expression data. Proceedings of the Ninth International Conference on IAPR Stockholm, Sweden, 48–59.
  • Madeira, S. C., and A. L. Oliveira. 2004. Biclustering algorithms for biological data analysis: A survey. IEEE/ACM Transactions on Computational Biology and Bioinformatics 1:24–45. doi:10.1109/TCBB.2004.2.
  • Mitra, S., and H. Banka. 2006. Multi-objective evolutionary biclustering of gene expression data. Pattern Recognition 39:2464–77. doi:10.1016/j.patcog.2006.03.003.
  • Murali, T., and S. Kasif. 2003. Extracting conserved gene expression motifs from gene expression data. Pacific Symposium on Biocomputing, Boston University, United States, 77–88.
  • Nelder, J. A., and R. Mead. 1965. A simplex method for function minimization. Computer Journal 7:308–13. doi:10.1093/comjnl/7.4.308.
  • Prelic, A., Bleuler, S., Zimmermann, P., Buhlmann, P., Gruissem, W., and Hennig, L. 2006. A systematic comparison and evaluation of biclustering methods for gene expression data. Bioinformatics 22 (9):1122-1129.
  • Roy, S., D. K. Bhattacharyya, and J. K. Kalita. 2013. CoBi: Pattern based co-regulated biclustering of gene expression data. Pattern Recognition 34:1669–78. doi:10.1016/j.patrec.2013.03.018.
  • Saber, H. B., and M. Elloumi. 2015. Efficiently mining gene expression data via novel binary biclustering algorithms. Journal of Proteomics & Bioinformatics S9 (8). doi: 10.4172/jpb.S9-008.
  • Tanay, A., R. Sharan, and R. Shamir. 2009. Discovering statistically significant biclusters in gene expression data. BMC Bioinformatics 18:136–44. doi:10.1093/bioinformatics/18.suppl_1.S136.
  • Wang, Z., G. Li, and R. W. Robinson. 2016. UniBic: Sequential row-based biclustering algorithm for analysis of gene expression data’. Scientific Reports 6:23466. doi:10.1038/srep23466.
  • Wen, X., S. Fuhrman, G. S. Michaels, D. B. Carr, S. Smith, J. L. Barker, and R. Somogyi. 1998. Large-scale temporal gene expression mapping of central nervous system development. Proceedings of the National Academy of Sciences 95:334–39. doi:10.1073/pnas.95.1.334.
  • Yang, J., Wang, H., Wang, W., and Yu, P. 2003, ‘Enhanced biclustering on expression data’: proceedings of the Third IEEE Symposium on BioInformatics and BioEngineering, pp. 321-327.
  • Yang, X., Deb, S., and Fong, S. 2013. Metaheuristic Algorithms: Optimal Balance of Intensification and Diversification.
  • Yang, X. S., and S. Deb. 2009. Cuckoo search via Levy flights. Proceedings of World Congress on Nature & Biologically Inspired Computing 210–14.
  • Yin, L., and Y. Liu. 2017. Ensemble biclustering gene expression data based on the spectral clustering. Neural Computing and Applications 28:1–14.

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