部分论文信息如下：
1. H. Zhu, Y. Yang, Y. Wang, F. Wang, Y. Huang, Y. Chang, K. Wong*, X. Li*, Dynamic characterization and interpretation for protein–RNA interactions across diverse cellular conditions using HDRNet, Nature Communications, 2023. (IF= 17.694, Q1)
2. Z. Yu, Y. Su, Y. Lu, F. Wang, S. Zhang, Y. Chang, K. Wong*, X. Li*, Topological Identification and Interpretation for Single-cell Gene Regulation Elucidation across Multiple Platforms using scMGCA, Nature Communications, 2023. (IF= 17.694, Q1)
3. Y. Fan, Y. Wang, F. Wang, L. Huang, Y. Yang, K. Wong, X. Li*, Reliable Identification and Interpretation of Single-cell Molecular Heterogeneity and Transcriptional Regulation using Dynamic Ensemble Pruning, Advanced Science, 2023. (IF= 17.694, Q1)
4. Z. Zheng, J. Chen, X. Chen, L. Huang, W. Xie, Q. Lin, X. Li*, K. Wong*, Enabling Single-cell Drug Response Annotations from Bulk RNA- seq using SCAD, Advanced Science, 2023. (IF=17.521, Q1)
5. F. Wang, H. Alinejad-Rokny, J. Lin, T. Gao, X. Chen, L. Meng, X. Li*, K. Wong*, A lightweight framework for chromatin loop detection on single-cell Hi-C, Advanced Science, 2023. (IF= 17.521, Q1)
6. Y. Wang, Y. Zhu, S. Li, C. Bian, Y. Liang, K. Wong, X. Li*, scBGEDA: Deep Single-cell Clustering Analysis via a Dual Denoising Autoencoder with Bipartite Graph Ensemble Clustering, Bioinformatics, 2023. (IF=6.931,Q1)
7. P. Sun, S. Fan, S. Li, Y. Zhao, C. Lu*, K. Wong, X. Li*, Automated Exploitation of Deep Learning for Cancer Patient Stratification across Multiple Types, Bioinformatics, 2023. (IF=6.931,Q1)
8. Y. Su, F. Wang, S. Zhang, Y. Liang, K. Wong, X. Li*, scWMC: Weighted Matrix Completion-based Imputation of scRNA-seq Data via Prior Subspace Information, Bioinformatics, 2022. (IF=6.931,Q1)
9. F. Lu, Z. Yu, Y. Wang, Z. Ma, K. Wong, X. Li*, GMHCC: High-throughput Analysis of Biomolecular Data using Graph-based Multiple Hierarchical Consensus Clustering, Bioinformatics, 2022. (IF=6.931,Q1)
10. Y. Wang, Y. Yang, Z. Ma, K. Wong, X. Li*, EDCNN: Identification of Genome-Wide RNA-binding Proteins Using Evolutionary Deep Convolutional Neural Network, Bioinformatics, 2021. (IF=6.931, Q1)
11. X. Li, S. Zhang, K. Wong. Single-cell RNA-seq Interpretations using Evolutionary Multiobjective Ensemble Pruning, Bioinformatics, 2019. (IF=6.937, Q1)
12. Y. Wang, C. Bian, K. Wong, X. Li*, S. Yang*. Multiobjective Deep Clustering and Its Applications in Single-cell RNA-seq Data, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021. (IF=13.451, Q1)
13. Su, H. Zhu, K. Wong, Y. Chang, X. Li*, Hyperspectral Image Denoising via Weighted Multidirectional Low-rank Tensor Recovery, IEEE Transactions on Cybernetics, 2022. (IF=19.118,Q1)
14. Y. Wang, X. Li*, K. Wong, Y. Chang, S. Yang. Evolutionary Multiobjective Clustering Algorithms with Ensemble for Patient Stratification, IEEE Transactions on Cybernetics, 2021. (IF=19.118,Q1)
15. X. Li, S. Zhang, K. Wong. Multiobjective Genome-Wide RNA-Binding Event Identification from CLIP-seq Data, IEEE Transactions on Cybernetics, 2019. (IF=19.118,Q1)
16. X. Li, K. Wong. Evolutionary Multi-objective Clustering and Its Applications to Patient Stratification, IEEE Transactions on Cybernetics, 2018. (IF=19.118,Q1)
17. Y. Wang, Z. Hou, Y. Yang, K. Wong, X. Li*, Genome-wide Identification and Characterization of DNA Enhancers with a Stacked Multivariate Fusion Framework, PLOS Computational Biology, 2022. (Q1)
18. X. Li, S. Li, L. Huang, S. Zhang, K. Wong. High-throughput Single-cell RNA-seq Data Imputation and Characterization with Surrogate-assisted Automated Deep Learning, Briefings in Bioinformatics, 2021. (IF=13.994, Q1)
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19. Y. Cheng, Y. Su, Z. Yu, Y. Liang, K. Wong, X. Li*, Unsupervised Deep Embedded Fusion Representation of Single-cell Transcriptomics, Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2022. (Q1, Oral)
20. Z. Yu, Y. Lu, Y. Wang, F. Tang, K. Wong, X. Li*, ZINB-based Graph Embedding Autoencoder for Single-cell RNA-seq Interpretations, Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), 2021. (Q1, Oral)
21. M. Toseef, O. O. Petinrin, F. Wang, S. Rahaman, Z. Liu, X. Li*, K. Wong*, Deep transfer learning for clinical decision-making based on high-throughput data: comprehensive survey with benchmark results, Briefings in Bioinformatics, 2023. (IF=9.5, Q1)
22. Z. Hou, Y. Yang. Z. Ma, K. Wong, X. Li*, Learning the Protein Language of Proteome-wide Protein-protein Binding Sites via Explainable Ensemble Deep Learning, Communications Biology, 2022.
23. F. Wang, T. Gao, J. Lin, Z. Zheng, L. Huang, M. Toseef, X. Li*, K. Wong*, GILoop: robust chromatin loop calling across multiple sequencing depths on Hi-C data, iScience, 2022. (IF=6.107, Cell Press)
24. L. Huang, J. Lin, R. Liu, Z. Zhang, L. Meng, X. Chen, X. Li*, K. Wong*, CoaDTI: Multi-modal Co-attention based framework for drug-target interaction annotation, Briefings in Bioinformatics, 2022. (IF=13.994, Q1)
25. M. Toseef, X. Li*, K. Wong*, Reducing healthcare disparities using multiple multiethnic data distributions with fine-tuning of transfer learning, Briefings in Bioinformatics, 2022. (IF=11.622, Q1)
26. Y. Yang, Z. Hou, Y. Wang, H. Ma, P. Sun, Z. Ma, K. Wong, X. Li*, HCRNet: High-throughput circRNA-Binding Event Identification from CLIP-seq Data using Deep Temporal Convolutional Network, Briefings in Bioinformatics, 2022. (IF=11.622, Q1)
27. Y. Wang, K. Wong, X. Li*, Exploring High-throughput Biomolecular Data with Multiobjective Robust Continuous Clustering, Information Science, 2022.(Q1)
28. L. Huang, J. Lin, X. Li*, L. Song, Z. Zheng, and K. Wong*, EGFI: Drug-Drug Interaction Extraction and Generation with Fusion of Enriched Entity and Sentence Information, Briefings in Bioinformatics, 2021. (IF=11.622, Q1)
29. X. Li, S. Li, L. Huang, S. Zhang, K. Wong. High-throughput Single-cell RNA-seq Data Imputation and Characterization with Surrogate-assisted Automated Deep Learning, Briefings in Bioinformatics, 2021. (IF=11.622, Q1)
30. Z. Hou, Y. Yang, H. Li, K. Wong, X. Li*. iDeepSubMito: Identification of protein sub-mitochondrial localization with deep learning, Briefings in Bioinformatics, 2021. (IF=11.622, Q1)
31. Z. Yu, C. Bian, G. Liu, S. Zhang, K. Wong, X. Li*. Elucidating Transcriptomic Profiles from Single-cell RNA sequencing Data using Nature-Inspired Compressed Sensing, Briefings in Bioinformatics, 2021. (IF=11.622, Q1)
32. X. Li, S. Zhang, K. Wong. Deep Embedded Clustering with Multiple Objectives on scRNA-seq Data, Briefings in Bioinformatics, 2021. (IF=11.622, Q1)
33. Y. Yang, S. Li, Y. Wang, K. Wong, X. Li*. Identification of Haploinsufficient Genes from Epigenomic Data using Deep Forest, Briefings in Bioinformatics, 2020. (IF=11.622, Q1)
34. X. Li, S. Li, Y. Wang, S. Zhang, K. Wong. Identification of Pan-cancer Ras Pathway Activation with Deep Learning, Briefings in Bioinformatics, 2020. (IF=11.622, Q1)
35. Y. Yang, Z. Hou, Z. Ma, X. Li*, K. Wong*, iCircRBP-DHN: identification of circRNA-RBP interaction sites using deep hierarchical network, Briefings in Bioinformatics, 2020. (IF=11.622, Q1)
36. X. Li, K. Wong. Multiobjective Patient Stratification using Evolutionary Multiobjective Optimization. IEEE Journal of Biomedical and Health Informatics, doi.10.1109/JBHI.2017.2769711, 2017. (Q1)
37. X. Li, M. Li, Multiobjective Local Search algorithm based decomposition for Multiobjective Permutation Flowshop Scheduling Problem, IEEE Transactions on Engineering Management, 2015, 62(4): 544-557.(IF=6.146, Top journal for Engineering Management)
38. X. Li, S. Ma, Multi-objective Discrete Artificial Bee Colony Algorithm for Multi-objective Permutation Flow Shop Scheduling Problem with Sequence Dependent Setup Times, IEEE Transactions on Engineering Management, 64(2)(2016): 149-165. (IF=6.146, Top journal for Engineering Management)
39. X. Li, S. Zhang, K. Wong. Evolving Transcriptomic Profiles from Single-cell RNA-seq Data using Nature-Inspired Multiobjective Optimization, IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi. 10.1109/TCBB.2020.2971993, 2020.
40. Y. Wang, Q. Ma, K. Wong, X. Li*. Evolving Multiobjective Cancer Subtype Diagnosis from Cancer Gene Expression Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi.10.1109/TCBB.2020.2974953, 2020.
41. X. Li, K. Wong. Single-Cell RNA-seq Data Interpretation by Evolutionary Multiobjective Clustering, IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi.10.1109/TCBB.2019.2906601, 2019.
42. X. Li, S. Zhang, K. Wong. Nature-Inspired Multiobjective Epistasis Elucidation from Genome-Wide Association Studies, IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi. 10.1109/TCBB.2018.2849759, 2018.
43. X. Li, K. Wong. Elucidating Genome-Wide Protein-RNA Interactions using Differential Evolution, IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi. 10.1109/TCBB.2017.2776224, 2017.
44. X. Li, K. Wong, A Comparative Study for Identifying the Chromosome-Wide Spatial Clusters from High-Throughput Chromatin Conformation Capture data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, doi: 10.1109/TCBB.2017.2684800, 2017.
45. Wong, K. C., Yan, S., Lin, Q., X. Li, & Peng, C. Deleterious Non-Synonymous Single Nucleotide Polymorphism Predictions on Human Transcription Factors. IEEE/ACM transactions on computational biology and bioinformatics. 2019.
46. X. Li, M. Yin, Multiobjective Binary Biogeography based Optimization based Feature Selection for Gene Expression Data, IEEE Transactions on NanoBioscience, 12 (4) (2013): 343- 353.
47. X. Li, S. Ma, K. Wong, Evolving Spatial Clusters of Genomic Regions from High-Throughput Chromatin Conformation Capture data, IEEE Transactions on NanoBioscience,16(6) (2017), 400-407.
48. Y. Wang, B. Liu, Z. Ma, K. Wong, X. Li*, Nature-Inspired Multiobjective Cancer Subtype Diagnosis, IEEE Journal of Translational Engineering in Health and Medicine, Accepted, 2019.
