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

• 2025.12:  🎉 One paper accepted by ACS Synthetic Biology.
• 2025.11:   One preprint has been submitted to bioRxiv.
• 2025.10:   One paper accepted by Computational Biology and Chemistry.
• 2025.10:  🤗 I have been awarded the National Scholarship for Graduate Students（研究生国家奖学金）.
• 2025.08:   One paper accepted by Methods.
• 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

Nature Communications

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].

SCIENCE CHINA Information Sciences

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].

Neural Networks

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].

Information Sciences

Towards retraining-free RNA modification prediction with incremental learning.
Jianbo Qiao, Junru Jin, Haoqing Yu, Leyi Wei. Information Sciences, 2024. [CCF-B].

bioRxiv

Melody: Decoding the Sequence Determinants of Locus-Specific DNA Methylation Across Human Tissues.
Junru Jin#, Ding Wang#, Jianbo Qiao#, Wenjia Gao, Yuhang Liu, Siqi Chen, Quan Zou, Shu Wu, Ran Su, Leyi Wei. bioRxiv, 2025.

ACS Synthetic Biology

ABT-DDI: A Graph Transformer Model with Atomic-Bond Structure Awareness for Drug–Drug Interaction Prediction.
Xu Guo#, Jianbo Qiao#, Siqi Chen, Junru Jin, Ding Wang, Wenjia Gao, Feifei Cui, Zilong Zhang, Hua Shi, Zhongmin Yan, Leyi Wei, Xinbo Jiang. ACS Synthetic Biology, 2025.

• HGCPep: Hypergraph Deep Learning Identifies Cancer-associated Non-coding Peptides.
  Wentao Long, Zhongshen Li, Junru Jin, Jianbo Qiao, Yu Wang, Leyi Wei. Genomics, Proteomics & Bioinformatics, 2025.
• TK-DDI: Accurate and efficient drug-drug interaction prediction via token encoding.
  Yue Cheng#, Jianbo Qiao#, Siqi Chen, Leyi Wei, Guangmin Liang. Computational Biology and Chemistry, 2025.
• Accurate detection and quantification of single-base m6A RNA modification using nanopore signals with multi-view deep learning.
  Jun Zhang, Jianbo Qiao, Zhiqun Zhao, Chenglin Yin, Junru Jin, Ding Wang, Wenjia Gao, Leyi Wei. bioRxiv, 2025.
• Efficient RNA nucleotide encoding enhances the accurate prediction of ac4C modifications.
  Na Li*, Xiao Wang, Ming Zeng, Feng Cao, Ke Qiu, Jianbo Qiao*. Methods, 2025.
• MCAMEF-BERT: an efficient deep learning method for RNA N7-methylguanosine site prediction via multi-branch feature integration.
  Junlei Yu, Wenjia Gao, Siqi Chen, Ronglin Lu, Jianbo Qiao, Junru Jin, Leyi Wei, Hua Shi, Zilong Zhang, Feifei Cui, Xinbo Jiang, Zhongmin Yan. Briefings in Bioinformatics, 2025. [CCF-B].
• EDNTOM: An Ensemble Learning and Weight Mechanism-Based Nanopore Methylation Detection Tool.
  Ge Tian, Chenglin Yin, Jianbo Qiao, Ruheng Wang, Hua Shi, Feifei Cui, Zilong Zhang, Xinbo Jiang, Leyi Wei. ACS Omega, 2025.
• 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.
• 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.
• 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.

🎖 Honors and Awards

• 2025.10 National Scholarship for Graduate Students（研究生国家奖学金）.

💬 Invited Talks

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