Jianbo Qiao (乔剑博), a Ph.D. student at the School of Software Engineering, Shandong University. I graduated from Shandong University with a bachelor’s degree in software engineering in 2022. I am currently pursuing my Ph.D. in Professor Leyi Wei(魏乐义)’s research group (WeiLab). My research interests include artificial intelligence and bioinformatics, AI drug discovery, and genome sequence analysis.

🔥 News

• 2025.05:  🎉 One paper accepted by Science China Information Sciences [CCF-A].
• 2025.05:  🎉 One paper accepted by Neural Networks [CCF-B].
• 2025.04:  🎉 One paper accepted by Nature Communications [Nature子刊].
• 2024.01:  🎉 One paper accepted by Information Sciences [CCF-B].

📖 Educations

• 2024.09 - now, Artificial Intelligence, PhD student, Shandong University, Jinan, China.
• 2022.09 - 2024.06, Software Engineering, Master’s student, Shandong University, Jinan, China.
• 2018.09 - 2022.06, Software Engineering, Bachelor’s Degree, Shandong University, Jinan, China.

📝 Publications

• GICL: A Cross-Modal Drug Property Prediction Framework Based on Knowledge Enhancement of Large Language Models.
  Na Li, Jianbo Qiao, Fei Gao, Yanling Wang, Hua Shi, Zilong Zhang, Feifei Cui, Lichao Zhang, Leyi Wei. Journal of Chemical Information and Modeling, 2025.
• Molecular pretraining models towards molecular property prediction.
  Jianbo Qiao, Wenjia Gao, Junru Jin, Ding Wang, Xu Guo, Balachandran Manavalan, Leyi Wei. Science China Information Sciences, 2025. [CCF-A].
• Taco-DDI: accurate prediction of drug-drug interaction events using graph transformers and dynamic co-attention matrices.
  Jianbo Qiao, Xu Guo, Junru Jin, Ding Wang, Kefei Li, Wenjia Gao, Feifei Cui, Zilong Zhang, Hua Shi, Leyi Wei. Neural Networks, 2025. [CCF-B].
• A self-conformation-aware pre-training framework for molecular property prediction with substructure interpretability.
  Jianbo Qiao#, Junru Jin#, Ding Wang#, Saisai Teng, Junyu Zhang, Xuetong Yang, Yuhang Liu, Yu Wang, Lizhen Cui, Quan Zou, Ran Su, Leyi Wei. Nature Communications, 2025. [Nature子刊].
• MC-MSTLoc: Self-supervised Pre-training for Imbalanced Multi-label Protein Subcellular Localization Prediction Using Immunofluorescence Images.
  Fengsheng Wang, Jianbo Qiao, Xu Guo, Leyi Wei. IEEE Transactions on Computational Biology and Bioinformatics (TCBB), 2025. [CCF-B].
• Computational models for prediction of m6A sites using deep learning.
  Nan Sheng, Jianbo Qiao, Leyi Wei, Hua Shi, Huannan Guo, Changshun Yang. Methods, 2025.
• ERNIE-ac4C: A novel deep learning model for effectively predicting N4-acetylcytidine sites.
  Ronglin Lu, Jianbo Qiao, Kefei Li, Yanxi Zhao, Junru Jin, Feifei Cui, Zilong Zhang, Balachandran Manavalan, Leyi Wei. Journal of Molecular Biology, 2025.
• Moss-m7G: A motif-based interpretable deep learning method for RNA N7-methlguanosine site prediction.
  Yanxi Zhao, Junru Jin, Wenjia Gao, Jianbo Qiao, Leyi Wei. Journal of Chemical Information and Modeling, 2024.
• Towards retraining-free RNA modification prediction with incremental learning.
  Jianbo Qiao, Junru Jin, Haoqing Yu, Leyi Wei. Information Sciences, 2024. [CCF-B].
• NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection.
  Chenglin Yin, Ruheng Wang, Jianbo Qiao, Hua Shi, Hongliang Duan, Xinbo Jiang, Saisai Teng, Leyi Wei. Bioinformatics, 2024. [CCF-B].
• Multi-CGAN: deep generative model-based multiproperty antimicrobial peptide design.
  Haoqing Yu, Ruheng Wang, Jianbo Qiao, Leyi Wei. Journal of Chemical Information and Modeling, 2023.
• Deep Generative Models in De Novo Drug Molecule Generation.
  Chao Pang, Jianbo Qiao, Xiangxiang Zeng, Quan Zou, Leyi Wei. Journal of Chemical Information and Modeling, 2023.
• Rm-LR: a long-range-based deep learning model for predicting multiple types of RNA modifications.
  Sirui Liang, Yanxi Zhao, Junru Jin, Jianbo Qiao, Ding Wang, Yu Wang, Leyi Wei. Computers in Biology and Medicine, 2023.
• Clinical Phenotyping Prediction via Auxiliary Task Selection and Adaptive Shared-Space Correction.
  Xiao Yang, Ning Liu, Jianbo Qiao, Haitao Yuan, Teng Ma, Yonghui Xu, Lizhen Cui. CAAI International Conference on Artificial Intelligence (CICAI), 2022.

💬 Invited Talks

• Predicting RNA modifications without retraining through incremental learning. The Second CCF Bioinformatics “New Future” Young Scholars (BIO-3NEW) Symposium.2024.04.