X. Ma, Y. Yu, X. Li, Y. Qi, and Z. Zhu*, A survey of weight vector adjustment methods for decomposition based multi-objective evolutionary algorithms, IEEE Transactions on Evolutionary Computation, 2020. (accepted)
Z. Liang, H. Dong, C. Liu, W. Liang, and Z. Zhu*, Evolutionary multi-tasking for multi-objective optimization with subspace alignment and adaptive differential evolution, IEEE Transactions on Cybernetics, 2020. (accepted)
Z. Liang, T. Wu, X. Ma, Z. Zhu*, and S. Yang, A dynamic multi-objective evolutionary algorithm based on decision variable classification, IEEE Transactions on Cybernetics, 2020. (accepted)
Z. Liang, T. Luo, K. Hu, X. Ma, and Z. Zhu*, An indicator-based many-objective evolutionary algorithm with boundary protection, IEEE Transactions on Cybernetics, 2019. (accepted)
X. Ma, X. Li, Q. Zhang, K. Tang, Z. Liang, W. Xie, and Z. Zhu*, A survey on cooperative co-evolutionary algorithms, IEEE Transactions on Evolutionary Computation, vol. 23, no. 3, pp. 421-441, 2019.
Z. Liang, K. Hu, X. Ma, and Z. Zhu*, A many-objective evolutionary algorithm based on a two-round selection strategy, IEEE Transactions on Cybernetics, 2019 (in press).
R. Guo, Y.-R. Li, S. He, L. Ou-Yang, Y. Sun*, and Z. Zhu*, RepLong - de novo repeat identification using long read sequencing data, Bioinformatics, vol. 34, no. 7, pp. 1099-1107, 2018.
X. Ma, Q. Zhang, G. Tian, J. Yang, and Z. Zhu*, On Tchebycheff decomposition approaches for multi-objective evolutionary optimization, IEEE Transactions on Evolutionary Computation, vol. 22, no. 2, pp. 226-244, 2018.
Z.-H, You, Z.-A. Huang, Z. Zhu*, G.-Y. Yan, Z.-W. Li, Z. Wen, and X. Chen*, PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction, PLoS Computational Biology, vol. 13, no. 3, artical no. e1005455, 2017.
Z.-A. Huang, Z. Wen, Q. Deng, Y. Chu, Y. Sun, and Z. Zhu*,LW-FQZip 2: a parallelized reference-based compression of FASTQ files, BMC Bioinformatics, vol. 18, no. 1, pp. 179:1-179:8, 2017.
Z. Zhu, L. Li, Y. Zhang, Y. Yang, and X. Yang, CompMap: a reference-based compression program to speed up read mapping to related reference sequences, Bioinformatics, vol. 31, no. 3, pp. 426-428, 2015.
Z. Zhu, Y. Zhang, Z. Ji, S. He, and X. Yang, High-throughput DNA sequence data compression, Briefings in Bioinformatics, vol. 16, no. 1, pp. 1-15, 2015.
Y. Zhang, L. Li, Y. Yang, X. Yang, S. He and Z. Zhu*, Light-weight reference-based compression of FASTQ data, BMC Bioinformatics, vol. 16, pp.188, 2015.
Z. Zhu, J. Zhou, Z. Ji, and Y.-H. Shi, DNA sequence compression using adaptive particle swarm optimization-based memetic algorithm, IEEE Transactions on Evolutionary Computation, vol. 15, no. 5, pp. 643-558, 2011.
Z. Zhu, S. Jia, and Z. Ji, Towards a memetic feature selection raradigm, IEEE Computational Intelligence Magazine, vol. 5, no. 2, pp. 41-53, 2010.
Z. Zhu, Y. S. Ong and M. Zurada, Identification of full and partial class relevant genes, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no. 2, pp. 263-277, 2010.
Z. Zhu, Y. S. Ong and M. Dash, Markov blanket-embedded genetic algorithm for gene selection, Pattern Recognition, vol. 49, no. 11, pp. 3236-3248, 2007.
Z. Zhu, Y. S. Ong and M. Dash, Wrapper-filter feature selection algorithm using a memetic framework, IEEE Transactions On Systems, Man and Cybernetics - Part B:Cybernetics, vol. 37, no. 1, pp. 70-76, 2007.