Zhe Liu (刘喆)

Zhe Liu (刘喆)

Lecturer in Computer Science

Hi! I’m Zhe Liu (刘喆), and you can also call me Zelya (/ˈzæliə/).
I’m currently a Lecturer in the Department of Computer Science and Engineering, East China University of Science and Technology.
I received my Ph.D. in Biomedical Engineering at Shanghai Jiao Tong University (SJTU), supervised by Prof. Guan Ning Lin, also with academic guidance from Prof. Dong Xu. Prior to that, I received my B.Sc. in Computer Science from Northeast Normal University (NENU) in 2020, advised by Prof. Han Wang.

My research focuses on AI for Science, aiming to bridge computation and biomedicine through the development of interpretable, intelligent, and biologically meaningful models. Current interests include:

  • Variant effect prediction
  • Protein structure and interaction modeling
  • AI applications in Psychiatry

💌 I warmly welcome collaboration opportunities and invite students interested in my research to get in touch!

大家好，我是刘喆，现任华东理工大学 信息科学与工程学院 计算机系讲师，从事教学科研工作。
我的研究方向为AI for Science，致力于通过构建可解释、智能且具有生物学意义的模型，推动计算科学与生物医学的交叉发展。研究兴趣包括：

  • 突变效应预测
  • 蛋白质结构与相互作用建模
  • 人工智能在精神病学中的应用

💌 欢迎科研合作，也欢迎对我的研究方向感兴趣的同学联系我！

📂 Professional Experience

  • 2025.07 - Present
    Lecturer
    Department of Computer Science and Engineering, East China University of Science and Technology (ECUST), Shanghai, China

📖 Educations

  • 2020.09 - 2025.06
    Ph.D. in Biomedical Engineering
    School of Biomedical Engineering, Shanghai Jiao Tong University (SJTU), Shanghai, China
    Supervisor: Prof. Guan Ning Lin
    Also with academic mentorship from: Prof. Dong Xu
  • 2016-09 - 2020.06
    B.Sc. in Computer Science and Technology
    School of Information Science and Technology, Northeast Normal University (NENU), Changchun, China
    Academic Advisor: Prof. Han Wang

📝 Publications

2025

  • Zhe Liu, Yihang Bao, An Gu, Weichen Song, Guan Ning Lin*. Predicting the regulatory impacts of non-coding variants on gene expression through epigenomic integration across tissues and single-cell landscapes.
    Nature Computational Science, accepted. [link] (2025 IF=18.3)
  • Zhe Liu, An Gu, Yihang Bao, Guan Ning Lin*. Epigenetic impacts of non-coding mutations deciphered through pre-trained DNA language model at single-cell resolution.
    Advanced Science. [link] (2025 IF=14.1)
  • Weihao Li#, Zhe Liu#, Yihang Bao, Shunying Yu, Huafang Li, Guan Ning Lin*. Mutation-Drug Sensitivity Data Resource (MDSDR): A Comprehensive Resource for Studying and Addressing Drug Resistance.
    Frontiers of Computer Science. [link]) (2025 IF=4.6)
  • Zhe Liu#, Yihang Bao#, Wenhao Li#, Chengyi Yang, Weidi Wang, Wenxiang Cai, Guan Ning Lin*. Benchmarking the coding strategies of non-coding mutations on sequence-based downstream tasks with machine learning.
    BiorXiv preprint. [link] (Under Review)
  • Yihang Bao#, Zhe Liu#, Fangyi Zhao#, Wenhao Li, Hui Jin, Guan Ning Lin*. Memo-Patho: Bridging Local-Global Transmembrane Protein Contexts with Contrastive Pretraining for Alignment-Free Pathogenicity Prediction.
    BiorXiv preprint. [link]
  • Zhejun Kuang#, Yunkai Li#, Zhe Liu#, Jian Zhao, Lijuan Shi, Akira-Kawai, Han Wang*. Trends Assessment of the Genetic Mutation Induced Protein-Protein Interaction Variation via Protein Large Language Driven Method.
    BiorXiv preprint. [link]

2024

  • Zhe Liu#, Yihang Bao#, Shuai Zeng#, Ruiyi Qian, Miaohan Deng, An Gu, Jianye Li, Weidi Wang, Wenxiang Cai, Wenhao Li, Han Wang*, Dong Xu*, Guan Ning Lin*. Large Language Models in Psychiatry: Current Applications, Limitations, and Future Scope.
    Big Data Mining and Analytics. [link] (2024 IF=7.7)
  • Zhe Liu#, Yihang Bao#, Wenhaoi Li#, Jinwei Wu, Weidi Wang*, Guan Ning Lin*. MEMO-stab: Sequence-based Annotation of Mutation Effect on Transmembrane Protein Stability with Protein Language Model-Driven Machine Learning.
    2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2024).[link]
  • Zhe Liu#, Weidi Wang#, Mingxia Zhai#, An Gu, Shunying Yu*, Guan Ning Lin*. Predicting Psychosis Progression in Clinical High-Risk Individuals Using Peripheral Transcriptomic and Epigenomic Profiles: A Machine Learning Approach.
    2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2024).[link]
  • Weidi Wang#, Zhe Liu#, Daihui Peng, Guan Ning Lin*, Zhen Wang*. Genomic Insights into Genes Expressed Specifically During Infancy Highlight Their Dominant Influence on the Neuronal System.
    BMC Genomics. [link] (2024 IF=3.5)

2023

  • Zhe Liu#, Wei Qian#, Wenxiang Cai#, Weichen Song, Weidi Wang, Dhruba Tara Maharjan, Wenhong Cheng, Jue Chen, Han Wang, Dong Xu*, Guan Ning Lin*. MIPPI: Inferring the effects of protein variants on protein–protein interactions with interpretable transformer representations.
    Research. [link] (2023 IF=11)
  • Zhe Liu#, Yihang Bao#, Weidi Wang, Liangwei Pan, Han Wang*, Guan Ning Lin*. Emden: A novel method Intergrating Graph and Transformer Representation for Predicting the Effect of Mutations on Clinical Drug Response.
    Computers in Biology and Medicine. [link] (2023 IF=7.7)
  • Zhe Liu#, Mingxia Zhai#, Weichen Song, Yihang Bao, Wenxiang Cai, Guan Ning Lin*. Assessing the Polygenic Risk between Anxiety and Gut Microbiota Using Machine Learning.
    11th International Conference on Bioinformatics and Computational Biology (ICBCB 2023). [link]

2022

  • Zhe Liu#, Weihao Pan#, Weihao Li#, Xuyang Zhen, Jisheng Liang, Wenxiang Cai, Fei Xu, Kai Yuan, Guan Ning Lin*. Evaluation of the Effectiveness of Derived Features of AlphaFold2 on Single-Sequence Protein Binding Site Prediction.
    Biology. [link] (2022 IF=5.168)
  • Zhe Liu#, Weihao Pan#, Xuyang Zhen, Jisheng Liang, Wenxiang Cai, Guan Ning Lin*. Will AlphaFold2 be Helpful in Improving the Accuracy of Single-sequence PPI Site Prediction?
    10th International Conference on Bioinformatics and Computational Biology (ICBCB 2022). [link]
  • Weihao Pan#, Zhe Liu#, Weichen Song, Xuyang Zhen, Kai Yuan, Fei Xu*, Guan Ning Lin*. An Integrative Segmentation Framework for Cell Nucleus of Fluorescence Microscopy.
    Genes. [link] (2022 IF=4.141)

2021

  • Zhe Liu, Yingli Gong, Yihang Bao, Yuanzhao Guo, Han Wang*, Guan Ning Lin*. TMPSS: A Deep Learning-Based Predictor for Secondary Structure and Topology Structure Prediction of Alpha-helical Transmembrane Proteins.
    Frontiers in Bioengineering and Biotechnology. [link] (2021 IF=5.89)
  • Zhe Liu, Yingli Gong, Yuanzhao Guo, Xiao Zhang, Chang Lu, Li Zhang*, Han Wang*. TMP-SSurface2: A Novel Deep Learning-Based Surface Accessibility Predictor for Transmembrane Protein Sequence.
    Frontiers in Genetics. [link] (2021 IF=4.599)
  • Weihao Pan#, Zhe Liu#, Guan Ning Lin*. ASW-Net: A Deep Learning-based Tool for Cell Nucleus Segmentation of Fluorescence Microscopy.
    10th International Conference on Bioinformatics and Biomedical Science (ICBBS 2021). [link]

🎖 Honors and Awards

  • 2025 Outstanding Graduate of Shanghai Jiao Tong University
  • 2024 China National Scholarship (for Doctoral Students)
  • 2021 Aired Scholarship, Shanghai Jiao Tong University
  • 2020 President’s Scholarship, Northeast Normal University
  • 2018 President’s Scholarship, Northeast Normal University
  • 2017 China National Scholarship (for Undergraduates)

😄 Academic Activities

  • 2025.05 11th National Conference on Computational Biology and Bioinformatics (NCCBB 2025), Session Report
  • 2025.04 CCF Bioinformatics “BIO-3NEW” Youth Scholars Forum, Session Report
  • 2024.12 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2024), Regular Paper(1), Short Paper(1), Video Presentation
  • 2024.11 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB 2024), Poster
  • 2024.06 32nd Conference on Intelligent Systems for Molecular Biology (ISMB 2024), Poster (second author)
  • 2023.10 12th Chinese Conference on Bioinformatics & Systems Biology (CCBSB 2023), Poster, Third Place
  • 2023.07 CCF Bioinformatics “BIO-3NEW” Youth Scholars Forum, Session Report
  • 2023.04 11th International Conference on Bioinformatics and Computational Biology (ICBCB 2023), Full-Length Paper, Published in Proceedings
  • 2022.05 10th International Conference on Bioinformatics and Computational Biology (ICBCB 2022), Session Report, Full-Length Paper, Published in Proceedings
  • 2021.10 10th International Conference on Bioinformatics and Biomedical Science (ICBBS 2021), Full-Length Paper, Published in Proceedings
  • 2020.10 5th CCF Bioinformatics Conference (CBC 2020), Session Report
  • 2019.03 6th National Conference on Computational Biology and Bioinformatics (NCCBB 2019)

🔭 Academic Service

Academic Membership

  • Youth Committee Member, CCF BIO-3NEW (CCF生物信息学“BIO-3NEW”青年学者执委会委员)

Conference Committee

  • Program Committee Member, IEEE BIBM 2025

Journal Reviewer

  • Reviewer for Information Sciences
  • Reviewer for Frontiers of Computer Science

👔 Teaching

Shanghai Jiao Tong University

  • Spring 2021, Teaching Assistant, Fundamentals of Biomedical Statistics
  • Spring 2022, Teaching Assistant, Fundamentals of Biomedical Statistics