李向濤，吉林大學人工智慧學院教授，國家級青年人才，吉林省優青，吉林省創新拔尖人才。
基本介紹
- 中文名：李向濤
- 畢業院校：東北師範大學
- 學位/學歷：博士
- 專業方向：深度學習，生物信息學、演化計算、數據挖掘
- 職稱：教授
人物經歷,教育經歷,工作經歷,研究方向,主要成就,科研項目,論文,著作教材,榮譽表彰,社會任職,
人物經歷
教育經歷
2005.09 —— 2009.06 東北師範大學 本科
2009.09 —— 2012.06 東北師範大學 碩士
2012.09 —— 2015.06 東北師範大學 博士
工作經歷
2015.07 —— 2020.03東北師範大學信息科學與技術學院 副教授
2015.11 —— 2016.11 英國薩里大學 訪問學者
2017.03 —— 2019.04 香港城市大學 高級研究助理
2020.03 —— 吉林大學人工智慧學院 教授
研究方向
深度學習，生物信息學、演化計算、數據挖掘。
主要成就
2020-2022年連續3年入選史丹福大學全球前2%頂尖科學家榜單，主持國家自然科學面上基金和青年基金，吉林省青年和面上基金項目，國防先進技術類項目（創新基金），國防先進技術類項目各一項，縱向經費累積達到400萬元。以第一作者或通訊作者在學術期刊上發表相關論文約100篇，中科院一區及生物信息學頂級期刊約40篇，其中在綜合類頂級期刊Nature Communications和Advanced Science上發表論文6篇；在生物信息學頂級期刊發表論文20篇，包括Bioinformatics 6篇，PLoS Computational Biology 1篇，Briefings in Bioinformatics 12篇，Communications Biology 1篇；IEEE Trans系列期刊及CCF A類會議發表論文18篇，包括IEEE Transactions on Cybernetics 4篇，IEEE Transactions on Systems, Man, and Cybernetics: Systems 1篇，AAAI 2篇，IEEE/ACM Transactions on Computational Biology and Bioinformatics 6篇，IEEE Journal of Biomedical and Health Informatics 1篇，IEEE Transactions on NanoBioscience 2篇，IEEE Transactions on Engineering Management 2篇。
根據Google Scholar統計，論文被引用3600餘次，H-index=31。其中，一篇論文入選ESI高被引論文（被引頻次前1%），單篇引用最高次數300次，8篇論文引用次數超過100次。帶領團隊以第一完成人及第二完成人完成省級自然科學學術成果獎各一項。圍繞近年來國內外演化計算與無監督學習計算算法層面的工作進展，出版英文專著《Natural Computing for Unsupervised Learning》，由Springer 出版社出版。
科研項目
作為主持國家自然科學基金2項、吉林省自然科學基金2項，累計參與項目達10項。
1．國家高層次青年人才計畫項目，主持
1．吉林省優秀青年科技人才項目，主持
2. 國家自然科學基金委員會，面上項目，62076109，高維稀疏數據下進化深度聚類方法研究，2021-01至2024-12，59萬元，主持；
3. 國家自然科學基金委員會，青年項目，61603087，基於代理模型和層次進化算法的 多目標雙 層規劃問題研究，2017-01至2019-12，21萬元，主持；
4. 吉林省科技廳青年基金項目，20190103006JH，基於多目標群智慧型算法的混合調度問題研究，2019-01至2020-12，10萬元，主持；
5. 吉林省自然科學基金面上項目，20160101253JC，基於代理模型和層次進化算法的 雙層規劃問題研究2016-01至2018-12，10萬元，主持。
論文
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. 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)
8. 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)
9. 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)
10. 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)
11. 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)
12. X. Li, S. Zhang, K. Wong. Single-cell RNA-seq Interpretations using Evolutionary Multiobjective Ensemble Pruning, Bioinformatics, 2019. (IF=6.937, Q1)
13. 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)
14. 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)
15. 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)
16. 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)
17. X. Li, K. Wong. Evolutionary Multi-objective Clustering and Its Applications to Patient Stratification, IEEE Transactions on Cybernetics, 2018. (IF=19.118,Q1)
18. 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)
19. 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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20. 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)
21. 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)
22. 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)
23. 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.
24. 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)
25. 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)
26. 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)
27. 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)
28. Y. Wang, K. Wong, X. Li*, Exploring High-throughput Biomolecular Data with Multiobjective Robust Continuous Clustering, Information Science, 2022.(Q1)
29. 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)
30. 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)
31. 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)
32. 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)
33. X. Li, S. Zhang, K. Wong. Deep Embedded Clustering with Multiple Objectives on scRNA-seq Data, Briefings in Bioinformatics, 2021. (IF=11.622, Q1)
34. 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)
35. 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)
36. 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)
37. 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)
38. 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)
39. 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)
40. 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.
41. 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.
42. 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.
43. 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.
44. 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.
45. 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.
46. 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.
47. 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.
48. 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.
49. 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.
著作教材
Xiangtao, Li. & Ka-Chun, Wong. (2018). Natural Computing for Unsupervised Learning.
榮譽表彰
吉林省學術成果獎2項
吉林省科學技術獎二等獎1項
社會任職
副主編及編委：
BMC Biology (2023~, Top Journal)
BMC Bioinformatics (2022~)(CCF C, IF=3.328)
BMC Genomics (2022~)(CCF C, IF=4.558)
Current Gene Therapy(2021~)(SCI Index, IF=4.676)
PeerJ Computer Science(2021~) (SCI Index, IF=2.41)
Mini-Reviews in Medicinal Chemistry (2019~) (SCI Index, IF=2.842)
審稿：
Nature Communications, PNAS, American Journal of Human Genetics (AJHG), Advanced Science, Cell Genomics, Cell Reports Methods, Cell Reports Physical Science, Genome Biology, Bioinformatics, Briefings in Bioinformatics, PLoS Computational Biology, IEEE TPAMI, IEEE TKDE, IEEE TCYB, IEEE TNNLS, IEEE TEVC等期刊
