Hey all! I am Yanran Liu, a PhD student at the Department of Biomedical Sciences, City University of Hong Kong(香港城市大学). If you are seeking any form of academic cooperation, please feel free to email me at yanranliu7-c@my.cityu.edu.hk.
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🎓 I will be joining the CompBioClub in September 2026, under the supervision of Prof. Lingxi CHEN (陈凌曦).
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🔬 Currently, I am a Visiting Student Researcher at the School of Information Science and Technology, Great Bay University, supervised by Prof. Xubin ZHENG (郑旭彬).
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📚 I received my M.Sc. in Information Systems from City University of Hong Kong and my B.Eng. in Financial Engineering from Dalian Maritime University.
🔍 Research Interests
My research interests mainly include AI for Biomedical Science and Bioinformatics, specifically in:
- Spatial Multi-omics
- AI in Healthcare
- Online Biomedical Platforms
🔥 News
- 2026.02: 🎉 Our work on influenza prediction has been published in BMC Public Health!
- 2025.11: 🚀 Huge news! Our spatial multi-omics model, GROVER, has been accepted by AAAI 2026!
- 2025.10: 🎊 Triple win at BIBM 2025! Thrilled to announce that our work BioLinkGPT is headed to BIBM 2025!
- 2025.10: ✨ Our project SVP has also been accepted by BIBM 2025!
- 2025.10: � Another win! Our gene regulatory relationship prediction model has been accepted by BIBM 2025.
- 2025.10: 🎓🥳 Celebrated my Master’s graduation at CityU HK! A wonderful journey comes to an end!
- 2024.12: 🎉 Our first spatial multi-omics model, PRAGA, was accepted by AAAI 2025!
- 2024.12: ✨ Back to the research frontline at GBU!
- 2024.09: 🎓 A new chapter begins! Officially started my Master’s journey at CityU HK.
- 2024.08: 👋 Temporarily bidding farewell to GBU. New adventures await!
- 2024.04: ⚓ Joined Great Bay University (GBU). This is where my research dream officially sets sail!
📝 Publications
Predicting Gene Regulatory Relationship in Cancer Using LLM and Graph Neural Network from Known Regulations
Yanran Liu, Dian Meng, Xinlei Huang, Yidi Wang, et al.
BIBM 2025(CCF-B Conference)
- Extracted gene regulatory relationships from 31,000+ PubMed abstracts using LLM to construct cancer-specific networks.
- Applied Magnetic Signed GNN for link prediction to discover novel regulatory relationships.
- Achieved SOTA performance with predictions validated by external cell line data.
Two-Stage Hybrid Model for Influenza Trend Forecasting and Key Driver Analysis
Yanran Liu, Jingxia Guo, Xubin Zheng, et al.
BMC Public Health(JCR Q1 Journal)
- Analyzed 2011-2023 influenza data in Xinjiang with demographic and virological drivers across pre/post-COVID periods.
- Developed LSTM-GBR hybrid model integrating key drivers via systematic feature engineering.
- Identified school-age cases and viral strain proportions as primary predictors of outbreak severity.
PRAGA: Prototype-aware Graph Adaptive Aggregation for Spatial Multi-modal Omics Analysis
Xinlei Huang, Zhiqi Ma, Dian Meng, Yanran Liu, et al.
AAAI 2025(CCF-A Conference)
- Proposed dynamic graph construction to capture latent semantic relations that fixed KNN graphs fail to model due to sequencing perturbations.
- Designed cross-modal learning module to integrate spatial information and denoise perturbations from sequencing.
- Introduced Bayesian GMM-based prototype contrastive learning to optimize representations without known class priors, achieving SOTA over 7 baselines.
- AAAI 2026 GROVER: Graph-guided Representation of Omics and Vision with Expert Regulation for Adaptive Spatial Multi-omics Fusion, Yongjun Xiao, Dian Meng, Xinlei Huang, Yanran Liu, et al.
- BIBM 2025 SVP: Support Vector Gene Pair as Biomarker Selection for Breast Cancer, Yijun Zhou, Qiyi Chen, Dian Meng, Yanran Liu, Jinchao Feng, Xubin Zheng.
- BIBM 2025 BioLinkGPT: Predicting Missing TF-target Gene Interactions Using Graph Neural Networks with Large Language Model, Zhihua Du, Weiliang Huang, Yanran Liu, et al.