张仲楠 教授、博士生导师

Ph.D.美国德克萨斯大学达拉斯分校计算机科学系,2008.08

研究方向:大数据分析,人工智能,深度学习,数据挖掘,生物信息学

电子邮件:zhongnan_zhang@xmu.edu.cn

个人主页:bioinfo.xmu.edu.cn

个人简历:

教育背景

Ph.D.美国德克萨斯大学达拉斯分校计算机科学系,2008.08
M.S.东南大学计算机科学与工程系,2001.06
B.S. 东南大学计算机科学与工程系,1999.06

工作经历

2019/6至今,厦门大学,我院软件工程系,教授、博士生导师
2018/11 - 2019/6,厦门大学,软件学院软件工程系,教授、博士生导师
2017/8 – 2018/11,厦门大学,软件学院软件工程系,教授
2012/8 – 2017/7,厦门大学,软件学院软件工程系,副教授
2009/12 - 2012/7,厦门大学,软件学院软件工程系,助理教授

研究领域

大数据分析,人工智能,深度学习,数据挖掘,生物信息学

演讲/授课

数据库系统(本科)、IT专业英语(本科)、大数据处理技术(研究生)、数据挖掘与数据仓库(研究生)

学术和社会兼职

福建省人工智能学会:理事

中国自动化学会智能健康与生物信息专业委员会委员

近期在研科研项目(持续更新中):

  1. 福建省科技计划引导性(重点)项目

  2. 贵州某企业管理集团委托项目(立项经费超过200万)

近期发表论文

  1. Yuxin Chen, Yuqi Wen, Chenyang Xie, Xinjian Chen, Song He*, Xiaochen Bo*, Zhongnan Zhang*. MOCSS: Multi-omics data clustering and cancer subtyping via shared and specific representation learning. ISCIENCE, Volume26, Issue8, 107378. (中科院2区, Cell旗下)

  2. Yuqi Wen, Linyi Zheng, Dongjin Leng, Chong Dai, Jing Lu, Zhongnan Zhang*, Song He*, and Xiaochen Bo*. Deep Learning-Based Multiomics Data Integration Methods for Biomedical Application. ADVANCED INTELLIGENT SYSTEMS, Volume5, Issue5, 2200247. (中科院3区)

  3. Peng Ke, Shuke Xiang, Chenyang Xie, Yunhao Zhang, Zhen He*, Zhongnan Zhang*. Unsupervised continual learning of single-cell clustering based on novelty detection and memory replay. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 3031-3038, Las Vegas, NV, United states. (EI, CCF B类)

  4. Dongjin Leng, Linyi Zheng, Yuqi Wen, Yunhao Zhang, Lianlian Wu, Jing Wang, Meihong Wang, Zhongnan Zhang*, Song He*, and Xiaochen Bo*. A benchmark study of deep learning-based multi-omics data fusion methods for cancer. GENOME BIOLOGY, 23, Article number: 171. (中科院1区 Top)

  5. Kanghao Shao, Yunhao Zhang, Yuqi Wen, Zhongnan Zhang*, Song He*, and Xiaochen Bo*. DTI-HETA: Prediction of drug-target interactions based on GCN and GAT on heterogeneous graph. Briefings in Bioinformatics, bbac109, https://doi.org/10.1093/bib/bbac109, 2022. (中科院2区, CCF B类)

  6. Jie Yang, Song He, Zhongnan Zhang*, Xiaochen Bo*. NegStacking: drug-target interaction prediction based on ensemble learning and logistic regression. IEEE-ACM Transactions on Computational Biology and Bioinformatics, 18(6), 2021, 2624-263. (中科院3区, CCF B类)

  7. Yihua Ye, Yuxin Chen, Zhongnan Zhang*, Yuqi Wen, Song He*, and Xiaochen Bo*. Drug-target interaction prediction based on non-negative and self-representative matrix factorization. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021, pp. 2352-2359, Houston, TX, USA. (EI, CCF B类)

  8. Peng Ke, Yuqi Wen, Zhongnan Zhang*, Song He*, Xiaochen Bo*. A Metagraph-Based Model for Predicting Drug-Target Interaction on Heterogeneous Network. 30th International Conference on Artificial Neural Networks (ICANN), LNCS 12891, pp. 465–476, 2021. https://doi.org/10.1007/978-3-030-86362-3_38 (EI, CCF C类)

  9. Xupeng Zou, Zhongnan Zhang*, Zhen He*, and Liang Shi*. Unsupervised Ensemble Learning with Noisy Label Correction. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’21), July 11-15, 2021, Virtual Event, Canada. ACM, New York, NY, USA. (EI, CCF A类)

  10. Jianjian Yan, Zhongnan Zhang*, Huailin Dong. AdaDT: An adaptive decision tree for addressing local class imbalance based on multiple split criteria. Applied Intelligence, 51, 4744–4761 (2021). (中科院2区, CCF C类)

  11. Kanghao Shao, Zhongnan Zhang*, Song He, Xiaochen Bo*. DTIGCCN: Prediction of drug-target interactions based on GCN and CNN, 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI), 337-342, Baltimore, MD, USA. (EI, CCF C类)

  12. Jianjian Yan, Zhongnan Zhang*, Kunhui Lin*, Fan Yang*, Xiongbiao Luo. A hybrid scheme-based one-vs-all decision trees for multi-class classification tasks, Knowledge-Based Systems, 198 (2020), 105922. (中科院1区 Top, CCF C类)

  13. Lingwei Xie, Song He, Zhongnan Zhang*, Kunhui Lin*, Xiaochen Bo*, Shu Yang, Boyuan Feng, Kun Wan, Kang Yang, Jie Yang, Yufei Ding. Domain-Adversarial Multi-Task Framework for Novel Therapeutic Property Prediction of Compounds, Bioinformatics, 36(9), 2020, 2848–2855. (中科院2区, CCF B类)

  14. Kang Yang, Zhongnan Zhang*, Song He and Xiaochen Bo*. Prediction of DTIs for high-dimensional and class-imbalanced data based on CGAN. 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) , 788-791, Madrid, Spain, 2018. (EI, CCF B类)

  15. Xiaoping Zheng, Song He, Xinyu Song, Zhongnan Zhang*, Xiaochen Bo*. DTI-RCNN: New efficient hybrid neural network model to predict drug–target interactions. 27th International Conference on Artificial Neural Networks (ICANN), LNCS 11139:104-114, 2018. (EI, CCF C类)

  16. Lingwei Xie, Song He, Xinyu Song, Xiaochen Bo*, Zhongnan Zhang*. Deep learning-based transcriptome data classification for drug-target interaction prediction, BMC genomics, 19, Suppl 7, 667, 2018.9.24. (中科院2区Top)

  17. Zhongnan Zhang*, Lei Hu, Ming Qiu, Fangyuan Gao. Events detection and community partition based on probabilistic snapshot for evolutionary social network, Peer-to-Peer Networking and Applications, 10(6), 1272–1284, 2017. (CCF C类)

  18. Lingwei Xie, Song He, Yuqi Wen, Xiaochen Bo*, Zhongnan Zhang*. Discovery of novel therapeutic properties of drugs from transcriptional responses based on multi-label classification, SCIENTIFIC REPORTS, 7, 7136, 2017. (中科院3区)

  19. Lingwei Xie, Zhongnan Zhang*, Song He, Xiaochen Bo*, Xinyu Song. Drug–target interaction prediction with a deep-learning-based model. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 469-476, 2017. (EI, CCF B类)

  20. Tingxi Wen, Zhongnan Zhang*, Kelvin K. L. Wong. Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation, PLOS ONE, 11(5), e0155176, 2016. (中科院3区)

  21. Lei Hu, Zhongnan Zhang*, Fangyuan Gao. Probabilistic Snapshot Based Evolutionary Social Network Events Detection. 10th International Conference on Mobile Ad-hoc and Sensor Networks, pp. 243-250, Maui, Hawaii, USA, 2014. (EI, CCF C类)

授权发明专利

  1. 一种基于区域候选框跟踪的视频目标定位方法. 第一发明人. ZL 201810111825.9

  2. 基于卷积网络和自编码的EEG信号无监督特征学习方法. 第一发明人. ZL 201810046404.2

  3. 通过WordNet嵌入进行测试和更新的树形网络方法. 第一发明人. ZL 201810517482.6

  4. 一种面向高维数据的特征选择方法. 第一发明人. ZL 201811580747.3