Cheng Liang(梁成)

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Personal Info

I am currently an Associate Professor in School of Information Science and Engineering, Shandong Normal University(山东师范大学). I obtained my MD degree and PhD degree in 2010 and 2015 from Hunan University(湖南大学), under the supervision of Prof. Renfa Li(李仁发 教授) and Prof. Jiawei Luo(骆嘉伟 教授), respectively. From 2012 to 2014, I studied in Donnelly Centre, University of Toronto, under the supervision of Prof. Zhaolei Zhang. I was awarded the Excellent Doctoral Dissertation of Hunan University in 2016. My current research interests include bioinformatics and machine learning.

Research Interests

  1. Multiview clustering
  2. Feature selection
  3. Machine learning

Funding

Selected Publications

  1. Guanghui Li, Peihao Bai, Jiao Chen, Cheng Liang*. Identifying virulence factors using graph transformer autoencoder with ESMFold-predicted structures. Computers in Biology and Medicine, 2024, 170: 108062.
  2. Wenlan Chen, Hong Wang, Cheng Liang*. Deep multi-view contrastive learning for cancer subtype identification. Briefings in Bioinformatics, 2023, 24(5): bbad282.
  3. Xuejing Shi, Juntong Zhu, Yahui Long*, Cheng Liang*. Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks. Briefings in Bioinformatics, 2023, 24(5): bbad278.
  4. Mingchao Shang, Cheng Liang*, Jiawei Luo, Huaxiang Zhang. Incomplete multi-view clustering by simultaneously learning robust representations and optimal graph structures. Information Sciences, 2023, 640: 119038.
  5. Cheng Liang, Lianzhi Wang, Li Liu, Huaxiang Zhang, Fei Guo*. Multi-view Unsupervised Feature Selection with Tensor Robust Principal Component Analysis and Consensus Graph Learning. Pattern Recognition, 2023, 141: 109632.
  6. Xiaofeng Shi, Cheng Liang*, Hong Wong. Multiview Robust Graph-Based Clustering for Cancer Subtype Identification. IEEE-ACM Transactions on Computational Biology and Bioinformatics. 2023, 20(1): 544-556.
  7. Lianzhi Wang, Cheng Liang*, Wenjiao Dong, Wenlan Chen. Multi-view Unsupervised Feature Selection via Consensus Guided Low-rank Tensor Learning. IEEE BIBM, 2022: 575-580. (acceptance rate 19.8%)
  8. Cheng Liang*, Mingchao Shang, Jiawei Luo*. Cancer subtype identification by consensus guided graph autoencoders. Bioinformatics, 2021, 37(24): 4779-4786.
  9. Haoran Liu#, Mingchao Shang#, Huaxiang Zhang*, Cheng Liang*. Cancer Subtype Identification based on Multi-view Subspace Clustering with Adaptive Local Structure Learning, IEEE BIBM, 2021, 484-490. (acceptance rate 19.6%)
  10. Fei Wang, Lei Zhu, Cheng Liang*, Jingjing Li, Xiaojun Chang, Ke Lu. Robust optimal graph clustering. Neurocomputing, 2020, 378: 153-165.
  11. Haojiang Tan, Quanmeng Sun, Guanghui Li, Qiu Xiao, Pingjian Ding, Jiawei Luo, Cheng Liang*. Multiview Consensus Graph Learning for lncRNA-Disease Association Prediction. Frontiers in Genetics, 2020, 11: 89.
  12. Qiu Xiao, Jiawei Luo, Cheng Liang, Guanghui Li, Jie Cai, Pingjian Ding, Ying Liu. Identifying lncRNA and mRNA Co-Expression Modules from Matched Expression Data in Ovarian Cancer. IEEE-ACM Transactions on Computational Biology and Bioinformatics, 2020, 17(2): 623-634. (2020 TCBB Best Paper Award)
  13. Ka-Chun Wong, Jiao Zhang, Shankai Yan, Xiangtao Li, Qiuzhen Lin, Sam Kwong, Cheng Liang. DNA Sequencing Technologies: Sequencing Data Protocols and Bioinformatics Tools. ACM Computing Surveys, 2019, 52(5): 98.
  14. Zhenxia Pan, Huaxiang Zhang*, Cheng Liang*, Guanghui Li, Qiu Xiao, Pingjian Ding, Jiawei Luo. Self-Weighted Multi-Kernel Multi-Label Learning for Potential miRNA-Disease Association Prediction. Molecular Therapy-Nucleic Acids, 2019, 17: 414-423.
  15. Cheng Liang*, Shengpeng Yu, Jiawei Luo*. Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs. PLoS Computational Biology, 2019, 15(4): e1006931.
  16. Ka-Chun Wong, Jiecong Lin, Xiangtao Li, Qiuzhen Lin, Cheng Liang, You-Qiang Song. Heterodimeric DNA motif synthesis and validations. Nucleic Acids Research, 2019, 47(4): 1628-1636.
  17. Shengpeng Yu, Cheng Liang*, Qiu Xiao, Guanghui Li, Pingjian Ding, Jiawei Luo. MCLPMDA: A novel method for miRNA-disease association prediction based on matrix completion and label propagation. Journal of Cellular and Molecular Medicine, 2019, 23(2): 1427-1438.
  18. Cheng Liang*, Shengpeng Yu, Ka-Chun Wong, Jiawei Luo*. A novel semi-supervised model for miRNA-disease association prediction based on l1-norm graph. Journal of Translational Medicine, 2018, 16: 357.
  19. Qiu Xiao, Jiawei Luo, Cheng Liang, Jie Cai, Pingjian Ding. A graph regularized non-negative matrix factorization method for identifying microRNA-disease associations. Bioinformatics, 2018, 34(2): 239-248. (Highly Cited Paper)
  20. Jie Cai, Cheng Liang*, Jiawei Luo. Feature selection using information distance measure for gene expression data. Current Proteomics, 2018, 15(5): 352-362.
  21. Cheng Liang, Yue Li, Jiawei Luo. A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging. IEEE-ACM Transactions on Computational Biology and Bioinformatics, 2016, 13(3): 549-556
  22. Cheng Liang, Yue Li, Jiawei Luo, Zhaolei Zhang. A novel motif-discovery algorithm to identify co-regulatory motifs in large transcription factor and microRNA co-regulatory networks in human. Bioinformatics, 2015, 31(14): 2348-2355
  23. Cheng Liang, Jiawei Luo, Dan Song. Network simulation reveals significant contribution of network motifs to the age-dependency of yeast protein-protein interaction networks. Molecular BioSystems, 2014, 10: 2277-2288
  24. Cheng Liang, Jiawei Luo, Renfa Li, NguyenHoang Tu. A Visual Representation for RNA Secondary Structure and Its Application. International Journal of Quantum Chemistry, 2012, 112 (10): 2243-2255
  25. Yue Li, Cheng Liang(co-first author), Ka-Chun Wong, Jiawei Luo, Zhaolei Zhang. Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion. Bioinformatics, 2014, 30 (18): 2627-2635
  26. Yue Li, Cheng Liang(co-first author), Steve Easterbrook, Jiawei Luo, Zhaolei Zhang. Investigating the functional implications of reinforcing feedback loops in transcriptional regulatory networks. Molecular BioSystems, 2014, 10: 3238-3248
  27. Yue Li, Cheng Liang, Ka-Chun Wong, Ke Jin, Zhaolei Zhang. Inferring probabilistic miRNA-mRNA interaction signatures in cancers: a role-switch approach. Nucleic Acids Research, 2014, 42 (9): e76