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. Su, Z. Yu, Y. Yang, X. Li*, Distribution-agnostic Deep Learning Enables Accurate Single‐Cell Data Recovery and Transcriptional Regulation Interpretation, Advanced Science, 2024. (IF= 17.521, Q1)
4. 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)
5. 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)
6. 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)
7. N. Chen, J. Yu, Z. Liu, L. Meng, X. Li*, K. Wong*, Discovering DNA shape motifs with multiple DNA shape features: generalization, methods, and validation, Nucleic Acids Research, 2024, (IF = 14.9, Q1)
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8. 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)
9. 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)
10. 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)
11. 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)
12. 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)
13. X. Li, S. Zhang, K. Wong. Single-cell RNA-seq Interpretations using Evolutionary Multiobjective Ensemble Pruning, Bioinformatics, 2019. (IF=6.937, Q1)
14. 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)
15. 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)
16. 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)
17. 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)
18. X. Li, K. Wong. Evolutionary Multi-objective Clustering and Its Applications to Patient Stratification, IEEE Transactions on Cybernetics, 2018. (IF=19.118,Q1)
19. 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)
20. 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)
21. 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)
22. 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)
23. 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)
24. 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.
25. 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)
26. 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)
27. 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)
28. 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)
29. Y. Wang, K. Wong, X. Li*, Exploring High-throughput Biomolecular Data with Multiobjective Robust Continuous Clustering, Information Science, 2022.(Q1)
30. 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)
31. 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)
32. 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)
33. 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)
34. X. Li, S. Zhang, K. Wong. Deep Embedded Clustering with Multiple Objectives on scRNA-seq Data, Briefings in Bioinformatics, 2021. (IF=11.622, Q1)
35. 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)
36. 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)
37. 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)
38. 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)
39. 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)
40. 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)
41. 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.
42. 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.
43. 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.
44. 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.
45. 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.
46. 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.
48. 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.
49. 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.
50. 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.
