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,信息学院软件工程系,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