Jun Liu

Jun Liu

Postdoctoral Research Fellow

Hi, I’m Jun Liu (刘俊). I am currently a Postdoctoral Research Fellow at ZhangLab, Cancer Science Institute of Singapore (CSI), National University of Singapore (NUS), under the supervision of Prof. Yang Zhang. I received my Ph.D. in Control Science and Engineering from Zhejiang University of Technology (China), where I was advised by Prof. Guijun Zhang.

My research interests focus on AI-driven computational structural biology, including protein structure prediction and model quality assessment, protein–protein and antibody–antigen interaction modeling, and therapeutic antibody design and engineering.

🔥 News

💰 Funding

  • Genome-Wide Antibody–Antigen Interaction Prediction Through Large Language Models. National Medical Research Council (NMRC), Singapore — Open Fund – Young Individual Research Grant (OF-YIRG). Award No. MOH-OFYIRG25jan-0011. 01 Aug 2025 – 31 Jul 2028 (PI).

🎓 Mentoring

Visiting PhD Students
  • Qihang Zhen, Zhejiang University of Technology, China. Visiting at NUS, supported by my OF-YIRG project (2026.02–present).
Undergraduate Students
  • Puhuan Zhu, Faculty of Science, NUS (2025.10–present).
  • Roger Lim Bo Zu, School of Computing, NUS (2025.10–present).
  • Hungyu Chen, School of Computing, NUS (2024.04–2025.06).
  • Edison Siow Xiong, School of Computing, NUS (2024.03–2025.06).

📝 Publications (Selected)

† indicates equal contribution, * indicates the corresponding author.

  • Jun Liu, Hungyu Chen, Yang Zhang*. A paired sequence language model for protein-protein interaction modeling. Nature Communications, https://doi.org/10.1038/s41467-026-70457-5, 2026. [Server] [Source code]

  • Jun Liu, Guangxing He, Kailong Zhao, Xiaogen Zhou, Guijun Zhang*. De novo protein structure prediction by model quality assessment dynamic feedback mechanism using deep learning. IEEE Transactions on Computational Biology and Bioinformatics, 22(6): 3476-3485, 2025. [Paper]

  • Jun Liu, Dong Liu, Guijun Zhang*. DeepUMQA3: A web server for accurate assessment of interface residue accuracy in protein complexes. Bioinformatics, 39(10): btad591, 2023. [Paper] [Server]

  • Jun Liu, Dong Liu, Guangxing He, Guijun Zhang*. Estimating protein complex model accuracy based on ultrafast shape recognition and deep learning in CASP15. Proteins: Structure, Function, and Bioinformatics, 91(12): 1861-1870, 2023. [Paper]

  • Jun Liu, Kailong Zhao, Guijun Zhang*. Improved model quality assessment using sequence and structural information by enhanced deep neural networks. Briefings in Bioinformatics, 24(1): bbac507, 2022. [Paper]

  • Jun Liu, Kailong Zhao, Guangxing He, Liujing Wang, Xiaogen Zhou, Guijun Zhang*. A de novo protein structure prediction by iterative partition sampling, topology adjustment, and residue-level distance deviation optimization. Bioinformatics, 38(1): 99-107, 2022. [Paper]

  • Jun Liu, Xiaogen Zhou, Yang Zhang*, Guijun Zhang*. CGLFold: A contact-assisted de novo protein structure prediction using global exploration and loop perturbation sampling algorithm. Bioinformatics, 36(8): 2443–2450, 2020. [Paper]

  • Guangxing He†, Jun Liu†, Dong Liu, Guijun Zhang*. GraphGPSM: A global scoring model for protein structure using graph neural networks. Briefings in Bioinformatics, 24(4): bbad219, 2023. [Paper]

  • Saisai Guo†, Jun Liu†, Xiaogen Zhou, Guijun Zhang*. DeepUMQA: Ultrafast shape recognition-based protein model quality assessment using deep learning. Bioinformatics, 38(7): 1895-1903, 2022. [Paper]

  • Dong Liu, Jun Liu, Haodong Wang, Fang Liang, Guijun Zhang*. DeepUMQA-X: Comprehensive and insightful estimation of model accuracy for protein single-chain and complex. Nucleic Acids Research, 53(W1): W219–W227, 2025. [Paper]

  • Dong Liu, Biao Zhang, Jun Liu, Hui Li, Le Song, Guijun Zhang*. Assessing protein model quality based on deep graph coupled networks using protein language model. Briefings in Bioinformatics, 25(1): bbad420, 2024. [Paper]

  • Qiongqiong Feng, Minghua Hou, Jun Liu, Kailong Zhao, Guijun Zhang*. Construct a variable-length fragment library for de novo protein structure prediction. Briefings in Bioinformatics, 23(3): bbac086, 2022. [Paper]

  • Kailong Zhao, Jun Liu, Xiaogen Zhou, Jianzhong Su*, Yang Zhang*, Guijun Zhang*. MMpred: A distance-assisted multimodal conformation sampling for de novo protein structure prediction. Bioinformatics, 37(23): 4350-4356, 2021. [Paper]

  • Liujing Wang, Jun Liu, Yuhao Xia, Jiakang Xu, Xiaogen Zhou, Guijun Zhang*. Distance-guided protein folding based on generalized descent direction. Briefings in Bioinformatics, 22(6): bbab296, 2021. [Paper]

  • Xiaogen Zhou, Chunxiang Peng, Jun Liu, Yang Zhang*, Guijun Zhang*. Underestimation-assisted global-local cooperative differential evolution and the application to protein structure prediction. IEEE Transactions on Evolutionary Computation, 24(3): 536-550, 2020. [Paper]

🎖 Honors and Awards

  • 2024 🥇 Ranked #1 in protein complex interface residue identification at CASP16 (group: MQA).
  • 2024 🥇 Ranked #1 in QMODE 3 (MassiveFold model selection) for monomer at CASP16 (group: MQA).
  • 2023 Outstanding Ph.D. Thesis Award, Zhejiang Society for Bioinformatics.
  • 2022 🥇 Ranked #1 in protein complex local quality assessment at CASP15 (group: GuijunLab-RocketX).
  • 2022 Top Ten Academic Stars (Graduate Students), Zhejiang University of Technology.
  • 2021 National Scholarship for Doctoral Students (China).
  • 2019 Second Prize, 16th “Challenge Cup” National Undergraduate Extracurricular Academic & Technology Competition (China). (Member rank: 1/8)
  • 2019 Gold Award, 5th Zhejiang “Internet+” Innovation and Entrepreneurship Competition (China). (Member rank: 2/11)
  • 2014 Third Prize, National Finals, China 3D Digitalization Innovation Design Competition (China). (Member rank: 3/3)

🧾 Academic Service

  • Topic Editor, Frontiers Research Topic: Computer-Aided Approaches in Translational Structural Biology: Toward Future Biotechnological Applications (Frontiers in Chemical Biology).
  • Reviewer for Nature biotechnology, Nature machine intelligence, PloS one, etc.