一、个人简介

邱望仁，博士后，三级教授，硕士生导师，现任信息工程学院副院长。从事的科学研究主要涉及模糊数学理论和生物数据挖掘工作。任中国现场统计研究会大数据统计分会理事，中国计算机学会生物信息学专委委员，中国计算机学会生物医学数据挖掘与计算专委委员，江西省现场统计学会、江西省数学学会等多个学术学会的理事。2021年和2022年入选“全球前2%顶尖科学家榜单”。

二、研究方向

生物信息学、陶瓷信息等相关数据的统计分析与挖掘。

三、教学与科研成果

近五年主持的主要科研项目：

江西省教育厅科研课题一般项目《基于多模态数据融合的蛋白质复合物链间接触图预测》（GJJ2400905），立项时间2024年，5万元，主持人：刘子，本人参与。

景德镇市科技局项目《融合多源生物特征与深度学习的蛋白质复合物链间接触图精准预测》（2025JCYJ003），立项时间2025年，3万，主持人：刘子，本人参与。

江西省高等教育科学研究规划课题一般课题：《基于“三分一合”路径的高校人工智能通识课程建设与数字素养培养研究》（ ZN-D-009），立项时间2025年，本人主持。

景德镇市科学技术协会科技创新自选课题《人工智能赋能的景德镇国家陶瓷文化传承创新试验区旅游文化与经济协同发展研究》（2024KJCXZXKT14），立项时间2024年，1000元，主持人：刘子，本人参与。

景德镇科技局《景德镇市生物大数据重点实验室（提升计划）》（20234PTYH001），（景财教指（2023）83号文），5.5万元，2024.1-2025.12，本人主持。

江西省社会科学规划办公室：2023年度江西省智库研究项目：《景德镇陶瓷文化影响力研究》（23ZK03）， 一般项目，2万，本人主持。

江西省学位与研究生教育教学改革研究项目《基于OBE理念和学科竞赛培训的理工科创新人才培养研究与实践》（JXYJG-2022-164），2022.6-2024.6，结题，1万，本人主持。

江西省教育厅科研重点项目《肿瘤诊断中的智能计算方法及应用研究》（GJJ2201004），2023.1-2024.12,  5万，本人主持。

国家自然科学基金地区项目《基于多源信息融合的肿瘤标志物识别方法研究》（62162032），2022.1-2025.12，37万元，本人主持。

江西省自然科学基金面上项目《基于多源信息整合和智能计算技术的生物序列修饰若干问题研究》（20202BAB202007），2020.1-2022.12，6万，本人主持。

景德镇市科学技术局工业科技技术一般项目《融合多策略特征筛选的基因组修饰位点预测》（20192GYZD008-04），2019.01-2021.12，3万，主持人：许召春，本人参与。

江西省教育厅科研重点项目《多源信息融合的生物序列特征及应用研究》（GJJ180703），2019.1-2021.12，5万，本人主持。

国家自然科学基金项目《基于不平衡多标签数据处理技术的蛋白质修饰若干问题研究》（ 31760315），2018.1-2021.12，41万，本人主持。

近年发表的论文、论著：

Liu, Z., W.R. Qiu, Y. Liu, H. Yan, W. Pei, Y.H. Zhu, and J. Qiu, A comprehensive review of computational methods for Protein-DNA binding site prediction. Anal Biochem, 2025. 703: p. 115862.

Li, Y.-Y., Z. Liu, X. Liu, Y.-H. Zhu, C. Fang, M. Arif, and W.-R. Qiu, A Systematic Review of Computational Methods for Protein Post-Translational Modification Site Prediction. Archives of Computational Methods in Engineering, 2025.

Huang, R., W. Qiu, X. Xiao, and W. Lin, iProtDNA-SMOTE: Enhancing protein-DNA binding sites prediction through imbalanced graph neural networks. PLoS One, 2025. 20(5): p. e0320817.

Yu, L., Z. Xu, W. Qiu, and X. Xiao, MSDSE: Predicting drug-side effects based on multi-scale features and deep multi-structure neural network. Comput Biol Med, 2024. 169: p. 107812.

Yang, H., W. Qiu, and Z. Liu, Anoikis-related mRNA-lncRNA and DNA methylation profiles for overall survival prediction in breast cancer patients. Math Biosci Eng, 2024. 21(1): p. 1590-1609.

Qiu, W., Q. Liang, L. Yu, X. Xiao, W. Qiu, and W. Lin, LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach. Curr Pharm Des, 2024. 30(6): p. 468-476.

Lv, Z., X. Wei, S. Hu, G. Lin, and W. Qiu, iSUMO-RsFPN: A predictor for identifying lysine SUMOylation sites based on multi-features and feature pyramid networks. Anal Biochem, 2024. 687: p. 115460.

Lu, C.Y., Z. Liu, M. Arif, T. Alam, and W.R. Qiu, Integration of gene expression and DNA methylation data using MLA-GNN for liver cancer biomarker mining. Front Genet, 2024. 15: p. 1513938.

Jia, J., P. Lv, X. Wei, and W. Qiu, SNO-DCA: A model for predicting S-nitrosylation sites based on densely connected convolutional networks and attention mechanism. Heliyon, 2024. 10(1): p. e23187.

Zi, W., J. Song, W. Kong, J. Huang, C. Guo, W. He, Y. Yu, B. Zhang, W. Geng, X. Tan, Y. Tian, Z. Liu, M. Cao, D. Cheng, B. Li, W. Huang, J. Liu, P. Wang, Z. Yu, H. Liang, S. Yang, M. Tang, W. Liu, X. Huang, S. Liu, Y. Tang, Y. Wu, L. Yao, Z. Shi, P. He, H. Zhao, Z. Chen, J. Luo, Y. Wan, Q. Shi, M. Wang, D. Yang, X. Chen, F. Huang, J. Mu, H. Li, Z. Li, J. Zheng, S. Xie, T. Cai, Y. Peng, W. Xie, Z. Qiu, C. Liu, C. Yue, L. Li, Y. Tian, D. Yang, J. Miao, J. Yang, J. Hu, R.G. Nogueira, D. Wang, J.L. Saver, F. Li, Q. Yang, and R.B. Investigators, Tirofiban for Stroke without Large or Medium-Sized Vessel Occlusion. N Engl J Med, 2023. 388(22): p. 2025-2036.

Zeng, X., X. Zeng, Q. Zeng, Y. Wu, S. Zhang, Y. Yang, X. Zhu, W. Zhang, Y. Xu, X. Min, W. Chen, W. Zhou, and J. Qiu, The external jugular vein is a feasible and safe alternative access for retrieval of inferior vena cava filter. J Vasc Access, 2023. 24(6): p. 1489-1494.

Yu, L., Z. Xu, M. Cheng, W. Lin, W. Qiu, and X. Xiao, MSEDDI: Multi-Scale Embedding for Predicting Drug-Drug Interaction Events. Int J Mol Sci, 2023. 24(5).

Xia, W.T., W.R. Qiu, W.K. Yu, Z.C. Xu, and S.H. Zhang, Identifying TME signatures for cervical cancer prognosis based on GEO and TCGA databases. Heliyon, 2023. 9(4): p. e15096.

Wu, J.M., W.R. Qiu, Z. Liu, Z.C. Xu, and S.H. Zhang, Integrative approach for classifying male tumors based on DNA methylation 450K data. Math Biosci Eng, 2023. 20(11): p. 19133-19151.

Lou, L.L., W.R. Qiu, Z. Liu, Z.C. Xu, X. Xiao, and S.F. Huang, Stacking-ac4C: an ensemble model using mixed features for identifying n4-acetylcytidine in mRNA. Front Immunol, 2023. 14: p. 1267755.

Liu, Z.W., G. Chen, C.F. Dong, W.R. Qiu, and S.H. Zhang, Intelligent assistant diagnosis for pediatric inguinal hernia based on a multilayer and unbalanced classification model. Front Physiol, 2023. 14: p. 1105891.

Liu, Z., Y.H. Zhu, L.C. Shen, X. Xiao, W.R. Qiu, and D.J. Yu, Integrating unsupervised language model with multi-view multiple sequence alignments for high-accuracy inter-chain contact prediction. Comput Biol Med, 2023. 166: p. 107529.

Jia, J., M. Sun, G. Wu, and W. Qiu, DeepDN_iGlu: prediction of lysine glutarylation sites based on attention residual learning method and DenseNet. Math Biosci Eng, 2023. 20(2): p. 2815-2830.

Yu, L., W. Qiu, W. Lin, X. Cheng, X. Xiao, and J. Dai, HGDTI: predicting drug-target interaction by using information aggregation based on heterogeneous graph neural network. BMC Bioinformatics, 2022. 23(1): p. 126.

Yu, L., M. Cheng, W. Qiu, X. Xiao, and W. Lin, idse-HE: Hybrid embedding graph neural network for drug side effects prediction. J Biomed Inform, 2022. 131: p. 104098.

Qiu, W.R., B.B. Qi, W.Z. Lin, S.H. Zhang, W.K. Yu, and S.F. Huang, Predicting the Lung Adenocarcinoma and Its Biomarkers by Integrating Gene Expression and DNA Methylation Data. Front Genet, 2022. 13: p. 926927.

Qiu, W.R., M.Y. Guan, Q.K. Wang, L.L. Lou, and X. Xiao, Identifying Pupylation Proteins and Sites by Incorporating Multiple Methods. Front Endocrinol (Lausanne), 2022. 13: p. 849549.

Qiu, W., T. Wu, and P. Xue, Can Mobile Payment Increase Household Income and Mitigate the Lower Income Condition Caused by Health Risks? Evidence from Rural China. Int J Environ Res Public Health, 2022. 19(18).

Luo, Z., W. Su, L. Lou, W. Qiu, X. Xiao, and Z. Xu, DLm6Am: A Deep-Learning-Based Tool for Identifying N6,2'-O-Dimethyladenosine Sites in RNA Sequences. Int J Mol Sci, 2022. 23(19).

Luo, Z., L. Lou, W. Qiu, Z. Xu, and X. Xiao, Predicting N6-Methyladenosine Sites in Multiple Tissues of Mammals through Ensemble Deep Learning. Int J Mol Sci, 2022. 23(24).

Lin, W., S. Hu, Z. Wu, Z. Xu, Y. Zhong, Z. Lv, W. Qiu, and X. Xiao, iCancer-Pred: A tool for identifying cancer and its type using DNA methylation. Genomics, 2022. 114(6): p. 110486.

Jia, J., G. Wu, and W. Qiu, pSuc-FFSEA: Predicting Lysine Succinylation Sites in Proteins Based on Feature Fusion and Stacking Ensemble Algorithm. Front Cell Dev Biol, 2022. 10: p. 894874.

Jia, J., G. Wu, M. Li, and W. Qiu, pSuc-EDBAM: Predicting lysine succinylation sites in proteins based on ensemble dense blocks and an attention module. BMC Bioinformatics, 2022. 23(1): p. 450.

Zheng, J., X. Xiao, and W.R. Qiu, iCDI-W2vCom: Identifying the Ion Channel-Drug Interaction in Cellular Networking Based on word2vec and node2vec. Front Genet, 2021. 12: p. 738274.

Qiu, W.R., Q.K. Wang, M.Y. Guan, J.H. Jia, and X. Xiao, Predicting S-nitrosylation proteins and sites by fusing multiple features. Math Biosci Eng, 2021. 18(6): p. 9132-9147.

Qiu, W.R., Z. Lv, Y.Q. Hong, J.H. Jia, and X. Xiao, BOW-GBDT: A GBDT classifier combining with Artificial Neural Network for identifying GPCR-drug interaction based on wordbook learning from sequences. Frontiers in Cell and Developmental Biology, 2021. Omics Data Integration towards Mining of Phenotype Specific Biomarker in Cancers and Diseases: p. doi.org/10.3389/fcell.2020.623858.

Qiu, W.R., G. Chen, J. Wu, J. Lei, L. Xu, and S.H. Zhang, Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence. Comput Math Methods Med, 2021. 2021: p. 6652288.

Qiu, W., Z. Lv, X. Xiao, S. Shao, and H. Lin, EMCBOW-GPCR: A method for identifying G-protein coupled receptors based on word embedding and wordbooks. Comput Struct Biotechnol J, 2021. 19: p. 4961-4969.

Xiao, X., G.F. Xue, B. Stamatovic, and W.R. Qiu, Using Cellular Automata to Simulate Domain Evolution in Proteins. Front Genet, 2020. 11: p. 515.

Xiao, X., L.-W. Duan, G.-F. Xue, G. Chen, P. Wang, and W.-R. Qiu, MF-EFP: Predicting Multi-Functional Enzymes Function Using Improved Hybrid Multi-Label Classifier. IEEE Access, 2020. 8: p. 50276-50284.

Xiao, X., W.J. Chen, and W.R. Qiu, A Novel Prediction of Quaternary Structural Type of Proteins with Gene Ontology. Protein Pept Lett, 2020. 27(4): p. 313-320.

Wang, P., X. Huang, W. Qiu, and X. Xiao, Identifying GPCR-drug interaction based on wordbook learning from sequences. BMC Bioinformatics, 2020. 21(1): p. 150.

Qiu, W., Z. Lv, Y. Hong, J. Jia, and X. Xiao, BOW-GBDT: A GBDT Classifier Combining With Artificial Neural Network for Identifying GPCR-Drug Interaction Based on Wordbook Learning From Sequences. Front Cell Dev Biol, 2020. 8: p. 623858.

邱望仁, 模糊时间序列模型理论及应用研究. 2013年, 天津大学出版社.

教学科研成果获奖：

邱望仁（3/5）; 生物序列信息挖掘研究， 江西省人民政府， 自然科学， 省部二等奖， 2022（肖绚； 贾建华； 邱望仁； 程翔； 许召春）

邱望仁（5/5）; 基于多种伪氨基酸成分融合的蛋白质序列分类预测器研究， 江西省教育厅， 其他， 2011（肖绚； 王普； 吴志诚； 林卫中； 邱望仁）

四、研究生培养情况

可招收研究生专业方向：统计学、大数据及应用

指导研究生要求：

（1）欢迎有统计学、大数据、数学、管理科学与工程、控制科学与工程等专业背景的学子报考。

（2）本科基础不重要，只要入学后能努力、勤奋、坚韧、有毅力！

（3）现有稳定的研究团队，需要有团队协作精神，交流能力强。

往届研究生毕业及就业情况：

截止2025年6月，指导并毕业研究生22人，其中在高校任教15人，中学任教2人，互联网/科技企业研发公司就业3人，政府公务员2人。

五、联系方式

联系邮箱：qiuone@163.com