Publications – Xiaoyong Pan

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Selected publications

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(^ Correspondence author)

Yichong Li, Xiaoyong Pan^, Hong-Bin Shen, Yang Yang^. DRAG: Design RNAs as Hierarchical Graphs with Reinforcement Learning, Briefings in Bioinformatics 2025 (in press) </li>
Xiaoyong Pan, Yi Fang, Xiaojian Liu, Xiaoyu Guo, Hong-Bin Shen. RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning. BMC Biology 2025 (In press ) [Server]
Weimin Zhu, Xiaohan Ding, Hong-Bin Shen, Xiaoyong Pan^. Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models. Journal of Molecular Biology, 2025 (in press) [Server]
Yao Dai#, Manja Idorn#, Manutea C Serrero, Xiaoyong Pan, Emil A Thomsen, Ryo Narita, Muyesier Maimaitili, Xiaoqing Qian, Marie B Iversen, Line S Reinert, Rasmus K Flygaard, Muwan Chen, Xiangning Ding, Bao-cun Zhang, Madalina E Carter-Timofte, Lu Qing, Zhuofan Jiang, Yiye Zhong, Shuhui Zhang, Lintai Da, Jinwei Zhu, Mark Denham, Poul Nissen, Trine H Mogensen, Jacob Giehm Mikkelsen, Shen-Ying Zhang, Jean-Laurent Casanova, Yujia Cai^, Søren R Paludan^. TMEFF1 is a neuron-specific restriction factor for herpes simplex virus. Nature (2024, accepted)
Ying Xia, Xiaoyong Pan^, Hong-Bin Shen^. Heterogeneous sampled subgraph neural networks with knowledge distillation to enhance double-blind protein-compound interaction prediction. Structure, 2024 (in press) [Server]
Ying Xia, Xiaoyong Pan^, Hong-Bin Shen^. A comprehensive survey on protein-ligand binding site prediction. Current Opinion in Structural Biology, 2024 (in press)
Jiachen Li, Xiaoyong Pan, Ye Yuan, Hong-Bin Shen. TFvelo: gene regulation inspired RNA velocity estimation. Nature Communications, 2024 (in press)
Hailong Yang, Yue Chen, Yun Zuo, Zhaohong Deng, Xiaoyong Pan, Hong-Bin Shen, Kup-Sze Choi, and Dong-Jun Yu. MINDG: A drug-target interaction prediction method based on an integrated learning algorithm.Bioinformatics, 2024, btae147.
Hehe Wu, Xiaojian Liu, Yi Fang, Yang Yang, Yan Huang, Xiaoyong Pan^, Hong-Bin Shen^. Decoding protein binding landscape on circular RNAs with base-resolution Transformer models. Computers in Biology and Medicine, 2024 (in press)[Server]
Yuxuan Wang, Ying Xia, Junchi Yan, Ye Yuan, Hong-Bin Shen, Xiaoyong Pan^. ZeroBind: A protein-specific zero-shot predictor with subgraph matching for drug-target interactions. Nature Communications, 2023 (in press) [Server]
Ye Yuan, Qushuo Chen, Jun Mao, Guipeng Li, Xiaoyong Pan. DG-Affinity: predicting antigen–antibody affinity with language models from sequences. BMC Bioinformatics 2023 (in press)
Ying Xia, Xiaoyong Pan^, Hong-Bin Shen^. LigBind: identifying binding residues for over 1000 ligands with relation-aware graph neural networks. Journal of Molecular Biology, 2023 (in press) [Server]
Yi Fang, Xiaoyong Pan^, Hong-Bin Shen^. De Novo Drug Design by Iterative Multi-Objective Deep Reinforcement Learning with Graph-based Molecular Quality Assessment. Bioinformatics, 2023(in press) [Code]
Zhinuo Zhou, Ge-Yi Fu, Yi Fang, Ye Yuan, Hong-Bin Shen, Chun-Sheng Wang, Xue-Wei Xu, Peng Zhou^ and Xiaoyong Pan^. EchoAI: a deep-learning based model for classification of echinoderms in global oceans. Front. Mar. Sci. - Ocean Observation, 2023(in press) [Server]
Chunqiu Xia, Shi-Hao Feng, Ying Xia, Xiaoyong Pan^, Hong-Bin Shen^. Leveraging Scaffold Information to Predict Protein-ligand Binding Affinity with an Empirical Graph Neural Network. Briefings in Bioinformatics, 2022(in press) [Server]
Ying Xia, Chun-Qiu Xia, Xiaoyong Pan^, Hong-Bin Shen^. BindWeb: a web server for ligand binding residue and pocket prediction from protein structures. Protein Science, 2022 (in press).[Server]
Jiachen Li, Siheng Chen, Xiaoyong Pan, Ye Yuan, Hong-Bin Shen.Cell clustering for spatial transcriptomics data with graph neural networks. Nature Computational Science, 2022 (in press).
Qunzhuo Wu, Zhaohong Deng, Xiaoyong Pan, Hong-Bin Shen, Kup-Sze Choi, Shitong Wang, Jing Wu, and Dong-Jun Yu. MDGF-MCEC: A multi-view dual attention embedding model with cooperative ensemble learning for circRNA-disease association prediction. Briefings in Bioinformatics, 2022 (in press).
Yong-Xian Fan^, Guicong Sun, Xiaoyong Pan^.ELMo4m6A: a contextual language embedding-based predictor for detecting RNA N6-methyladenosine sites. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2022 (in press). [Code]
Chunqiu Xia, Shi-Hao Feng, Ying Xia, Xiaoyong Pan^, and Hong-Bin Shen^. Fast protein structure comparison through effective representation learning with contrastive graph neural networks. PLoS Computational Biology, 2022 (in press). [Server]
Yong-Xian Fan^, Meijun Chen, Xiaoyong Pan^. GCRFLDA: Scoring lncRNA-disease associations using graph convolution matrix completion with conditional random field. Briefings in Bioinformatics, 2021 (in press).
Hehe Wu, Xiaoyong Pan^, Yang Yang and Hong-Bin Shen^. Recognizing binding sites of poorly characterized RNA-binding proteins on circular RNAs using attention Siamese network. Briefings in Bioinformatics, 2021 (in press). [Code]
Hui Li, Zhaohong Deng, Haitao Yang, Xiaoyong Pan, Zhisheng Wei, Hong-Bin Shen, Kup Sze Choi, Lei Wang, Shitong Wang, and Jing Wu. circRNA-binding protein sites prediction based on multi-view deep learning, subspace learning and multi-view classifier. Briefings in Bioinformatics, 2021 (in press). [Code]
Cheng-Peng Zhou, Di Wang, Xiaoyong Pan, and Hong-Bin Shen. Protein structure refinement using multi-objective particle swarm optimization with decomposition strategy. International Journal of Molecular Sciences, 2021 (in press). [Code]
Xiaoyong Pan^, Lei Chen, Ｍin Liu, Zhibin Niu, Tao Huang, Yu-Dong Cai. Identifying protein subcellular locations with embeddings-based node2loc. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021, in press. [Code]
Yang Lin, Xiaoyong Pan^, and Hong-Bin Shen^. lncLocator 2.0: a cell-line-specific subcellular localization predictor for long non-coding RNAs with interpretable deep learning. Bioinformatics, 2021, In press. [Server]
Ying Xia, Chunqiu Xia, Xiaoyong Pan^, and Hong-Bin Shen^. GraphBind: protein structural context embedded rules learned by hierarchical graph neural networks for recognizing nucleic-acid-binding residues. Nucleic Acids Research, 2021, In press. [Server]
Xiaoyong Pan^, Yi Fang, Xianfeng Li, Yang Yang, and Hong-Bin Shen. RBPsuite: RNA-protein binding sites prediction suite based on deep learning. BMC Genomics, 2020, In press. [Server]
Xiaoyong Pan^, Jasper Zuallaert, Xi Wang, Hong-Bin Shen, Elda Posada Campos, Denys O. Marushchak, Wesley De Neve. ToxDL: Deep learning using primary structure and domain embeddings for assessing protein toxicity. Bioinformatics, 2020, In press. [Server] [Code]
Sikai Ling, Shiqi Yang, Xinde Hu, Di Yin, Yao Dai, Xiaoqing Qian, Dawei Wang, Xiaoyong Pan, Jiaxu Hong, Xiaodong Sun, Hui Yang, Soren Riis Paludan and Yujia Cai. Lentiviral delivery of co-packaged Cas9 mRNA and a Vegfa-targeting guide RNA prevents wet age-related macular degeneration in mice. Nature Biomedical Engineering, 2020, in press.
Haitao Yang, Zhaohong Deng, Xiaoyong Pan, Hong-bin Shen, Kup-Sze, Choi, Lei Wang, Shitong Wang, Jing Wu. RNA-binding protein recognition based on multi-view deep feature and multi-label learning. Briefings in Bioinformatics, 2020, In press. [Server] [Code]
Wei-Xun Zhang, Xiaoyong Pan, Hong-Bin Shen. Signal-3L 3.0: Improving signal peptide prediction through combining attention deep learning with window-based scoring. Journal of Chemical Information and Modeling, 2020, In press. [Server]
Xiaoyong Pan^, Hong-Bin Shen^. Scoring disease-microRNA associations by integrating disease hierarchy into graph convolutional networks. Pattern Recognition. 2020, In press.
Chun-Qiu Xia, Xiaoyong Pan, and Hong-Bin Shen. Protein-ligand binding residue prediction enhancement through hybrid deep heterogeneous learning of sequence and structure data. Bioinformatics, 2020 (in press). [Server]
Xiaoyong Pan^, Hong-Bin Shen^. Inferring disease-associated microRNAs using semi-supervised multi-label graph convolutional networks. iScience. 20: 265-277. [Code]
Kaiming Zhang*, Xiaoyong Pan*, Yang Yang, and Hong-Bin Shen. CRIP: predicting circRNA-RBP interaction sites using a codon-based encoding and hybrid deep neural networks. RNA, 2019 (in press) (shared first author). [Code]
Xiaoyong Pan, Yang Yang, Chun-Qiu Xia, Aashiq H. Mirza, and Hong-Bin Shen. Recent Methodology and Progress of Deep learning for RNA-protein interaction prediction. WIREs RNA, 2019, in press.
Jasper Zuallaert, Xiaoyong Pan, Yvan Saeys, Xi Wang and Wesley De Neve. Investigating the biological relevance in trained embedding representations of protein sequences. ICML Workshop on Computational Biology 2019.
Xiaoyong Pan, Kai Xiong, Christian Anthon, Poul Hyttel, Kristine Freude, Lars Juhl Jensen, Jan Gorodkin. WebCircRNA: Classifying the circular RNA potential of coding and noncoding RNA . Genes. 2018, 9(11), 536. [Webserver]
Xiaoyong Pan, Lars Juhl Jensen, Jan Gorodkin. Inferring disease-associated long non-coding RNAs using genome-wide tissue expression profiles. Bioinformatics. In press. [Code]
Xiaoyong Pan, XiaoHua Hu, Yu-Hang Zhang, Lei Chen, LiuCun Zhu, ShiBao Wan, Tao Huang, Yu-Dong Cai. Identification of the Copy Number Variant Biomarkers for Breast Cancer Subtypes. Molecular Genetics and Genomics. 2018, 294: 95–110
Xiaoyong Pan^, Yong-Xian Fan, Jue Jia, Hong-Bin Shen^. Identifying RNA-binding proteins using multi-label deep learning. SCIENCE CHINA Information Sciences. 2019, 62(1). [Code]
Xiaoyong Pan, Anne Wenzel, Lars Juhl Jensen, Jan Gorodkin. Genome-Wide Identification of Clusters of Predicted MicroRNA Binding Sites as MicroRNA Sponge Candidates. Plos One. 2018, 13(8): e0202369. [Webserver]
Xiaoyong Pan^, Hong-Bin Shen^. Predicting RNA-protein binding sites and motifs through combining local and global deep convolutional neural networks. Bioinformatics. 2018, 34: 3427–3436. [Code]
Xiaoyong Pan^, Peter Rijnbeek, Junchi Yan, Hong-Bin Shen^. Prediction of RNA-protein sequence and structure binding preferences using deep convolutional and recurrent neural networks. BMC Genomics, 2018, 19:511.[Code]
Zhen Cao*, Xiaoyong Pan*, Yang Yang*, Yan Huang, Hong-Bin Shen^. The lncLocator: a subcellular localization predictor for long non-coding RNAs based on a stacked ensemble classifier. Bioinformatics, 2018, 34(13):2185-2194 (shared first author). [Webserver]
Xiaoyong Pan^, Hong-Bin Shen^. Learning distributed representations of RNA sequences and its application for predicting RNA-protein binding sites with a convolutional neural network. Neurocomputing. 2018, 305: 51-58. [Code]
Lei Chen*, Xiaoyong Pan*, XiaoHua Hu*, Yu-Hang Zhang, ShaoPeng Wang, Tao Huang, Yu-Dong Cai. Gene expression differences among different MSI statuses in colorectal cancer. International Journal of Cancer. In press (shared first author).
Yong-Xian Fan, Xiaoyong Pan, Yang Zhang^ and Hong-Bin Shen^. LabCaS for ranking potential calpain substrate cleavage sites from amino acid sequence. Methods in Molecular Biology, In press [Webserver]
Xiaoyong Pan^, Junchi Yan. Attention based convolutional neural network for predicting RNA-protein binding sites. NIPS Workshop on Machine Learning in Computational Biology, 2017. [Code]
Lei Chen, Yu-Hang Zhang, Guohua Huang, Xiaoyong Pan, ShaoPeng Wang, Tao Huang, Yu-Dong Cai. Discriminating circRNAs from other lncRNAs using a hierarchical extreme learning machine (H-ELM) algorithm with feature selection. Molecular Genetics and Genomics. 2017 Sep 14. doi: 10.1007/s00438-017-1372-7.
Xiaoyong Pan^, Hong-Bin Shen^. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach . BMC bioinformatics, 2017, 18(1):136. [Code]
Alexander Junge, Jan C. Refsgaard, Christian Garde, Xiaoyong Pan, Alberto Santos, Ferhat Alkan, Christian Anthon, Christian von Mering, Christopher T. Workman, Lars Juhl Jensen, and Jan Gorodkin. RAIN: RNA-protein Association and Interaction Networks. Database (Oxford), 2017, baw167.
Xiaoyong Pan, Yong-Xian Fan, Junchi Yan, Hong-Bin Shen. IPMiner: hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction. BMC genomics, 2016, 17(1): 582.
Xiaoyong Pan, Hong-Bin Shen. OUGENE: a disease associated over-expressed and under-expressed gene database. Science Bulletin, 2016, 61(10):752-754.
Xiaoyong Pan^, Kai Xiong. PredcircRNA: computational classification of circular RNA from other long non-coding RNA using hybrid features. Molecular BioSystems, 2015, 11(8): 2219-2226.
Aashiq H Mirza, Claus HB Berthelsen, Stefan E Seemann, Xiaoyong Pan, Klaus S Frederiksen, Mogens Vilien, Jan Gorodkin, Flemming Pociot. Transcriptomic landscape of lncRNAs in inflammatory bowel disease. Genome medicine, 2015, 7(1):39.
Xiaoyong Pan^, Lin Zhu, Yong-Xian Fan, Junchi Yan. Predicting protein–RNA interaction amino acids using random forest based on submodularity subset selection. Computational biology and chemistry, 2014, 53,:324-330.
Xiao-Yong Pan, Ye Tian, Yan Huang, Hong-Bin Shen. Towards better accuracy for missing value estimation of epistatic miniarray profiling data by a novel ensemble approach. Genomics, 2011, 97(5): 257-264.
Ya-Nan Zhang, Xiao-Yong Pan, Yan Huang, Hong-Bin Shen. Adaptive compressive learning for prediction of protein–protein interactions from primary sequence. Journal of theoretical biology, 2011, 283(1): 44-52.
Xiao-Yong Pan, Ya-Nan Zhang, Hong-Bin Shen. Large-Scale prediction of human protein− protein interactions from amino acid sequence based on latent topic features. Journal of Proteome Research, 2010, 9(10): 4992-5001.
Xue-Mei Ding, Xiao-Yong Pan, Chen Xu, Hong-Bin Shen. Computational prediction of DNA-protein interactions: a review. Current computer-aided drug design, 2010, 6(3): 197-206.
Xiao-Yong Pan, Hong-Bin Shen. Robust prediction of B-factor profile from sequence using two-stage SVR based on random forest feature selection. Protein and peptide letters, 2009, 16 (12), 1447-1454.

Xiaoyong Pan, Peter Rijnbeek. Hybrid deep learning for predicting hypertensive disorder onset using temporal and non-temporal data . OHDSI Symposium, 2017. [Poster]

Peter Rijnbeek, Xiaoyong Pan, Jenna M. Reps. Do we really need ‘Big Data” for patient-level predictive modelling? . OHDSI Symposium, 2017.[Poster]. Best contribution award to OHDSI 2017

Xiaoyong Pan, Hong-Bin Shen. A novel deep learning-based method for predicting RNA-protein interactions . Atlas of Science, 2017.

Reviewer

Leading guest Editor Special issue Sequential Data Modeling and Its Emerging Applications in IEEE Access.

Organizers for Correspondence Problem in Computer Vision and Pattern Recognition in ICPR 2018.