Publications

At-a-Glance

• 160 + peer-reviewed articles
• 100 + first-/corresponding-author papers
• h-index 36 (Google Scholar, July 2025)
• Full list & metrics: Google Scholar · ORCID

*Corresponding authors marked with “*”.

🏆 Nature Communications

• 2025 G. Hao, Y. Fan, Z. Yu, Y. Su, H. Zhu, F. Wang, X. Chen, Y. Yang, G. Wang, K. Wong, X. Li*, “Topological Identification and Interpretation for Single-cell Epigenetic Regulation Elucidation in Multi-tasks using scAGDE,” Nature Communications (2025).
• 2023 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).
• 2023 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).

🔬 Advanced Science

• 2025 F. Wang, J. Lin, H. Alinejad-Rokny, W. Ma, L. Meng, L. Huang, J. Yu, N. Chen, Y. Wang, Z. Yao, W. Xie, K. Wong*, X. Li*, “Unveiling Multi-scale Architectural Features in Single-cell Hi-C Data using scCAFE,” Advanced Science (2025).
• 2024 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).
• 2024 Y. Yang, G. Li, K. Pan, W. Cao, Z. Zhang*, X. Li*, “Deciphering 3′-UTR-Mediated Gene Regulation Using Interpretable Deep Representation Learning,” Advanced Science (2024).
• 2024 Z. Yu, Y. Yang, X. Chen, K. Wong, Z. Zhang, Y. Zhao*, X. Li*, “Accurate Spatial Heterogeneity Dissection and Gene Regulation Interpretation for Spatial Transcriptomics using Dual Graph Contrastive Learning,” Advanced Science (2024).
• 2023 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).
• 2023 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).
• 2023 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).

🧬 Nucleic Acids Research

• 2025 W. Ma, F. Wang, Y. Fan, G. Hao, Y. Su, K. Wong, X. Li*, “DeepNanoHi-C: Deep Learning Enables Accurate Single-Cell Nanopore Long-read Data Analysis and 3D Genome Interpretation,” Nucleic Acids Research (2025).
• 2024 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).

Other peer‑reviewed journals

Bioinformatics

• 2024 Y. Zhang, Z. Yu, K. Wong, X. Li*, “Unraveling Spatial Domain Characterization in Spatially Resolved Transcriptomics with Robust Graph Contrastive Clustering,” Bioinformatics (2024).
• 2024 Y. Wang, H. Zhu, Y. Wang, Y. Yang, Y. Huang*, J. Zhang*, K. Wong, X. Li*, “EnrichRBP: An Automated and Interpretable Computational Platform for Predicting and Analyzing RNA-binding Protein Events,” Bioinformatics (2024).
• 2023 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).
• 2024 Q. Qi, Y. Wang, Y. Huang, Y. Fan*, X. Li*, “PredGCN: A Pruning-enabled Gene–Cell Net for Automatic Cell Annotation of Single-cell Transcriptome Data,” Bioinformatics (2024).
• 2023 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).
• 2022 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).
• 2022 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).
• 2021 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).
• 2019 X. Li*, S. Zhang, K. Wong, “Single-cell RNA-seq Interpretations using Evolutionary Multiobjective Ensemble Pruning,” Bioinformatics (2019).

Other Bioinformatics Journals

• 2022 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).
• 2022 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).
• 2021 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).
• 2021 Z. Hou, Y. Yang, H. Li, K. Wong, X. Li*, “iDeepSubMito: Identification of Protein Sub-mitochondrial Localization with Deep Learning,” Briefings in Bioinformatics (2021).
• 2021 Z. Yu, C. Bian, G. Liu, S. Zhang, K. Wong, X. Li*, “Elucidating Transcriptomic Profiles from Single-cell RNA-seq Data using Nature-Inspired Compressed Sensing,” Briefings in Bioinformatics (2021).
• 2021 X. Li*, S. Zhang, K. Wong, “Deep Embedded Clustering with Multiple Objectives on scRNA-seq Data,” Briefings in Bioinformatics (2021).
• 2020 Y. Yang, S. Li, Y. Wang, K. Wong, X. Li*, “Identification of Haploinsufficient Genes from Epigenomic Data using Deep Forest,” Briefings in Bioinformatics (2020).
• 2022 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).
• 2022 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).
• 2021 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).

IEEE Transactions & Other Q1 Journals

• 2022 Y. Su, H. Zhu, K. Wong, Y. Chang, X. Li*, “Hyperspectral Image Denoising via Weighted Multidirectional Low-rank Tensor Recovery,” IEEE Transactions on Cybernetics (2022).
• 2021 Y. Wang, X. Li*, K. Wong, Y. Chang, S. Yang, “Evolutionary Multiobjective Clustering Algorithms with Ensemble for Patient Stratification,” IEEE Transactions on Cybernetics (2021).
• 2019 X. Li*, S. Zhang, K. Wong, “Multiobjective Genome-Wide RNA-Binding Event Identification from CLIP-seq Data,” IEEE Transactions on Cybernetics (2019).
• 2018 X. Li*, K. Wong, “Evolutionary Multi-objective Clustering and Its Applications to Patient Stratification,” IEEE Transactions on Cybernetics (2018).
• 2022 Y. Cheng, Y. Su, Z. Yu, Y. Liang, K. Wong, X. Li*, “Unsupervised Deep Embedded Fusion Representation of Single-cell Transcriptomics,” AAAI 2023 (Oral) (2022).
• 2021 Z. Yu, Y. Lu, Y. Wang, F. Tang, K. Wong, X. Li*, “ZINB-based Graph Embedding Autoencoder for Single-cell RNA-seq Interpretations,” AAAI 2022 (Oral) (2021).