Contact Information:

Postal address: Shenzhen MSU-BIT University, 1 International University Park Road, Longgang District, 518172 Shenzhen, Guangdong Province, P.R. China.

Office: Room 333, Main Building.

Email: 6420250084@smbu.edu.cn

Working experience

2025.12-Present Associate Professor Shenzhen MSU-BIT University, China

2021.9-2025.12 Research Associate The Chinese University of Hong Kong, Shenzhen, China

2019.9-2021.8 Post-doc The Chinese University of Hong Kong, Shenzhen, China

Education

2016.9-2018.9 Joint Ph.D Biostatistics, Department of Neurology, Harvard Medical School, USA

2014.9-2019.7 Ph.D Mathematics, Department of Mathematics, Harbin Institute of Technology, China

2012.9-2014.7 M.Sc Computational Mathematics, Department of Mathematics, Harbin Institute of Technology, China

2006.9-2010.7 B.Sc Information and Computing Science, School of Mathematics Sciences, Heilongjiang University, China

Fundings

(1) National Natural Science Foundation of China, Young Scientists Fund (C Class), 12501693, Research on detection methods of niche-differential gene expression based on spatial transcriptomics data, 2026-01 to 2028-12, 300,000 RMB, host.

(2) Department of Science and Technology of Guangdong Province, Natural Science Foundation of Guangdong Province - general project, 2025A1515011685, Research on spatial transcriptome analysis method based on graph theory, 2025-01 to 2027-12, 100,000 yuan, host.

(3) Department of Science and Technology of Guangdong Province, Natural Science Foundation of Guangdong Province - general project, 2023A1515011861, Research on cell subtype identification method integrating single-cell transcriptome data and spatial transcriptome data, 2023-01 to 2025-12, 100,000 yuan, host.

(4) National Natural Science Foundation of China, General Project, 11971130, Research on Identification and Functional Analysis Methods of Long Non-Coding RNAs Associated with Parkinson’s Disease, 2020-01 to 2023-12, 520,000 RMB, Participation.

(5) National Natural Science Foundation of China, General Project, 32070659, Substrate-specific analysis of E3 ubiquitin ligase and its regulatory network in different cancers, 2021-01 to 2024-12, 580,000 RMB, Participation.

Publications

1.Pang Yuxuan, Wang Chunxuan, Zhang Yao-Zhong, Wang Zhuo, Seiya Imoto, and Lee Tzong-Yi. STForte: tissue context-specific encoding and consistency-aware spatial imputation for spatially resolved transcriptomics. Briefings in Bioinformatics, 2025, 26(2), bbaf174. (Impact factor：6.8; JCR Q1)

2.Li Songyun, Wang Zhuo*, and Huang Hsien-Da. Deciphering ovarian cancer heterogeneity through spatial transcriptomics, single-cell profiling, and copy number variations. Plos one, 2025,20(13): e0317115. (Impact factor：2.9; JCR Q1; *co-corresponding author)

3.Li Songyun, Wang Zhuo, and Huang Hsien-Da* and Lee Tzong-Yi*. Machine Learning-Based Characterization and Identification of Tertiary Lymphoid Structures Using Spatial Transcriptomics Data[J]. International Journal of Molecular Sciences, 2024, 25(7): 3887. (Impact factor：5.6; JCR Q1)

4.Gu Lingui, Chen Hualin, Geng Ruxu, Liang Tingyu, Chen Yihao, Wang Zhuo, Ye Liguo, Sun Mingjiang, Shi Qinglei, Wan Gui, Chang Jianbo, Wei Junji, Ma Wenbin, Xiao Jiashun, Bao Xinjie, and Wang Renzhi*. Endothelial pyroptosis-driven microglial activation in choroid plexus mediates neuronal apoptosis in hemorrhagic stroke rats[J]. Neurobiology of Disease, 2024, 201: 106695. (Impact factor：5.1; JCR Q1)

5.Wang Zhuo, Pang Yuxuan, Chung Chia-Ru, Wang Hsin-Yao, Cui Haiyan, Chiang Ying-Chih, Horng Jorng-Tzong, Lu Jang-Jih and Lee Tzong-Yi*. A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology[J]. Briefings in Bioinformatics, 2023, 24(6): bbad330. (Impact factor：6.8; JCR Q1)

6.Li Weimin, Wu Hao, Li Jinxia, Wang Zhuo, Cai Miao, Liu Xiaoli, and Liu Ganqiang*. Transcriptomic analysis reveals associations of blood-based A-to-I editing with Parkinson’s disease[J]. Journal of Neurology, 2023: 1-10. (Impact factor：6; JCR Q1)

7.Pang Yuxuan, Yao Lantian, Xu Jingyi, Wang Zhuo* and Tzong-Yi Lee*. Integrating transformer and imbalanced multi-label learning to identify antimicrobial peptides and their functional activities[J]. Bioinformatics, 2022, 38(24): 5368-5374. (Impact factor：5.8; JCR Q1; * co-corresponding author)

8.Jhong Jhih-Hua, Yao Lantian, Pang Yuxuan, Li Zhongyan, Chung Chia-Ru, Wang Rulan, Li Shangfu, Li Wenshuo, Luo Mengqi, Ma Renfei, Huang Yuqi, Zhu Xiaoning, Zhang Jiahong, Feng Hexiang, Cheng Qifan, Wang Chunxuan, Xi Kun, Wu Li-Ching, Chang Tzu-Hao, Horng Jorng-Tzong, Zhu Lizhe, Chiang Ying-Chih, Wang Zhuo* and Lee Tzong-Yi*. dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data[J]. Nucleic Acids Research, 2022, 50(D1): D460-D470. (Impact factor：14.9; JCR Q1; * co-corresponding author)

9.Li Zhongyan, Li Shangfu, Luo Mengqi, Jhong Jhih-Hua, Li Wenshuo, Yao Lantian, Pang Yuxuan, Wang Zhuo, Wang Rulan, Ma Renfei, Yu Jinhan, Huang Yuqi, Zhu Xiaoning, Cheng Qifan, Feng Hexiang, Zhang Jiahong, Wang Chunxuan, Hsu Justin Bo-Kai, Chang Wen-Chi, Wei Feng-Xiang*, Huang Hsien-Da*, and Lee Tzong-Yi*. dbPTM in 2022: an updated database for exploring regulatory networks and functional associations of protein post-translational modifications[J]. Nucleic acids research, 2022, 50(D1): D471-D479. (Impact factor：14.9; JCR Q1)

10.Chen Yigang, Yao Lantian, Tang Yun, Jhong Jhih-Hua, Wan Jingting, Chang Jingyue, Cui Shidong, Luo Yijun, Cai Xiaoxuan, Li Wenshuo, Chen Qi, Huang His-Yuan, Wang Zhuo, Chen Weiming, Chang Tzu-Hao, Wei Fengxiang*, Lee Tzong-Yi* and Huang Hsien-Da*. CircNet 2.0: an updated database for exploring circular RNA regulatory networks in cancers[J]. Nucleic Acids Research, 2022, 50(D1): D93-D101. (Impact factor：14.9; JCR Q1)

11.Wang Chunxuan, Wang Zhuo, Wang Hsin-Yao, Chung Chia-Ru, Horng Jorng-Tzong, Lu Jang-Jih* and Lee Tzong-Yi*. Large-scale samples based rapid detection of ciprofloxacin resistance in Klebsiella pneumoniae using machine learning methods[J]. Frontiers in microbiology, 2022, 13: 827451. (Impact factor：6.064; JCR Q2)

12.Zhang Jiahong, Wang Zhuo, Wang Hsin-Yao, Chung Chia-Ru, Horng Jorng-Tzong, Lu Jang-Jih* and Lee Tzong-Yi*. Rapid antibiotic resistance serial prediction in staphylococcus aureus based on large-scale MALDI-TOF data by applying XGBoost in multi-label learning[J]. Frontiers in Microbiology, 2022, 13: 853775. (Impact factor：6.064; JCR Q2)

13.Wang Zhuo, Hsin-Yao Wang, Chia-Ru Chung, Horng Jorng-Tzong, Jang-Jih Lu, and Tzong-Yi Lee*. Large-scale mass spectrometry data combined with demographics analysis rapidly predicts methicillin resistance in Staphylococcus aureus. Briefings in Bioinformatics, 2021, 22(3): bbaa138. (Impact factor：13.994; JCR Q1)

14.Chung Chia-Ru^#, Wang Zhuo^#, Weng Jing-Mei, Wang Hsin-Yao, Wu Li-Ching, Tseng Yi-Ju, Chen Chun-Hsien, Lu Jang-Jih, Horng Jorng-Tzong and Lee Tzong-Yi*. MDRSA: A Web Based-Tool for Rapid Identification of Multidrug Resistant Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry[J]. Frontiers in Microbiology, 2021, 12: 3548. (Impact factor：6.064; JCR Q2; #co-first author)

15.Pang Yuxuan^#, Wang Zhuo^#, Jhih-Hua Jhong, and Tzong-Yi Lee*. Identifying anti-coronavirus peptides by incorporating different negative datasets and imbalanced learning strategies. Briefings in bioinformatics, 2021, 22(2):1085-1095.( Impact factor：13.994；JCR Q1; # co-first author)

16.Pang Yuxuan, Yao Lantian, Jhong Jhih-Hua, Wang Zhuo*, and Lee Tzong-Yi*. AVPIden: a new scheme for identification and functional prediction of antiviral peptides based on machine learning approaches. Briefings in Bioinformatics, 2021, 22(6),bbab263. (Impact factor：13.994；JCR Q1; * co-corresponding author)

17.Wan Yu, Wang Zhuo, and Tzong-Yi Lee*. Incorporating support vector machine with sequential minimal optimization to identify anticancer peptides. BMC bioinformatics, 2021(1): 1-16. (Impact factor：3；JCR Q3)

18.Wang Hsin-Yao, Chia-Ru Chung, Wang Zhuo, Shangfu Li, Bo-Yu Chu, Jorng-Tzong Horng, Jang-Jih Lu, and Tzong-Yi Lee*. A large-scale investigation and identification of methicillin-resistant Staphylococcus aureus based on peaks binning of matrix-assisted laser desorption ionization-time of flight MS spectra. Briefings in bioinformatics, 2021, 22(3): bbaa138. (Impact factor：13.994；JCR Q1)

19.Wang Hongfei^#, Wang Zhuo^#, Zhongyan Li, and Tzong-Yi Lee*. Incorporating deep learning with word embedding to identify plant ubiquitylation sites. Frontiers in Cell and Developmental Biology, 2020, 8:572195. (Impact factor：6.684；JCR Q1; # co-first author)

20.Wang Rulan^#, Wang Zhuo^#, Hongfei Wang, Yuxuan Pang, and Tzong-Yi Lee*. Characterization and identification of lysine crotonylation sites based on machine learning method on both plant and mammalian. Scientific reports, 2020,10(1): 1-12. (Impact factor：4.38；JCR Q2; # co-first author)

21.Chung Chia-Ru, Jhong Jhih-Hua, Wang Zhuo, Chen Siyu, Wan Yu, Horng Jorng-Tzong, and Lee Tzong-Yi*. Characterization and identification of natural antimicrobial peptides on different organisms. International journal of molecular sciences, 2020, 21(3): 986. (Impact factor：5.6；JCR Q1)

22.Wang Zhuo, Jin Shuilin, and Zhang Chiping*. A Method Based on Differential Entropy-Like Function for Detecting Differentially Expressed Genes Across Multiple Conditions in RNA-Seq Studies. Entropy, 2019, 21(3): 242. (Impact factor：2.7; JCR Q2)

23.Wang Zhuo, Jin Shuilin, Liu Guiyou, Zhang Xiurui, Wang Nan, Wu Deliang, Hu Yang, and Zhang Chiping*. DTWscore: differential expression and cell clustering analysis for time-series single-cell RNA-seq data. BMC Bioinformatics, 2017, 18(1): 270. (Impact factor：3;JCR Q3)

24.Jin Shuilin^#, Wang Zhuo^#, Lin Junyu, Wang Jia, Zhang Xiurui, Tan Renjie, Zhang Chuanbin, Wang Zhe, Guo Wanqian, Hu Yang, Xu Li, Zhang Lejun, Liu Guiyou, Jiang Qinghua*. The complexity of promoter regions based on a vector topological entropy. Current Bioinformatics, 2017, 12(5): 471-474. (Impact factor：4; JCR Q1; ^# co-first author)

25.Ye Zhe, Zhao Lingling, Wang Zhuo, Ma Peijun, Su Xiaohong*, Michael Pecht, and Pang Long. A dual-level approach for lithium-ion battery RUL prognosis. In 2015 IEEE Conference on Prognostics and Health Management (PHM), 2015, IEEE.