Zhang Yongqing, Doctor of Engineering, Associate Professor;
Email: zhangyq@cuit.edu.cn
Research and postgraduate enrollment direction:
1. Artificial Intelligence and Data Mining
2. Machine Learning and Bioinformatics
Profile:
Jointly trained by Sichuan University and the University of California, San Diego (UCSD, University of California, San Diego), he has long been engaged in applied research in machine learning, data mining, bioinformatics and brain computer interface. Presided over and participated in 8 scientific research projects including the National Natural Science Foundation of China, the Science and Technology Commission of the Military Commission, and the China Postdoctoral Fund. At present, he has published more than 40 SCI and EI papers in influential journals and international conferences at home and abroad, and applied for 5 invention patents. High quality journals include: Nuclear Acids Research, Briefings in Bioinformatics, Expert Systems with Applications, BMC Genomics, BMC Bioinformatics, Engineering Applications of Artificial Intelligence, International Journal of Machine Learning and Cybernetics, Chemicals and Intelligent Laboratory, Journal of Automation, Journal of University of Electronic Science and Technology of China, etc. At present, he is a member of the Bioinformatics Professional Committee of the Chinese Computer Society, a member of the Computer Application Professional Committee, a vice chairman of the YOCSEF Chengdu Sub Forum, a member of the Intelligent Health and Bioinformatics Professional Committee of the Chinese Association of Automation, a member of the Bioinformatics and Artificial Life Professional Committee of the Chinese Association of Artificial Intelligence, a member of the Council of the Sichuan Bioinformatics Society, a project reviewer of the National Foundation Committee, TCBB, NCAA Briefings in Bioinformatics, IEEE J BIOMED HEALTH, IEEE ACCESS, J BIOINF COMPUT BIOL and other journal reviewers.
Undertake scientific research projects:
1. Project leader of the Young Scientists Fund of the National Natural Science Foundation of China, research on the application of high-throughput data and deep learning in the construction of gene regulatory hierarchical network (61702058).
2. Research on Spiking Neural Network Learning Algorithm Driven by Membrane Voltage (2017M612948), general fund of China Postdoctoral Science Foundation, project leader.
3. Scientific Research Fund for Young and Middle aged Academic Leaders of Chengdu University of Information Engineering, Research on Gene Network Based on Intelligent Computing (J201706), project leader.
4. The Military Commission Science and Technology Commission Innovation Special Zone sub project, emotion feedback regulation system (2018Z007), the main research.
5. The sub project of the Special Zone of Innovation of the Science and Technology Commission of the Military Commission, the real-time generation system of brainwave music (2018Z130), the main research.
Current teaching:
"Principles of Computer Composition", undergraduate
"Artificial intelligence", undergraduate/postgraduate
Representative papers in recent 5 years (* is the corresponding author):
1. Yongqing Zhang, Zixuan Wang, Yuanqi Zeng, Yuhang Liu, Shuwen Xiong, Maocheng Wang, Jialiu Zhou, Quan Zou *, A new revolution attraction model for prediction translation factor binding sites by combination of sequence and shape, Briefings in Bioinformatics, Volume 23, Issue 1, 2022, bbab525
2. Yongqing Zhang, Zixuan Wang, Yuhang Liu, and Quan Zou *, By hybrid neural networks for prediction and interpretation of transfer factor binding sites based on multi economics, 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021, pp. 594-599. (CCF Class B Conference)
3. Yongqing Zhang, Qingyuan Chen, Meiqin Gong, Yuanqi Zeng, Dongrui Gao*, Gene regulatory networks analysis of muscle-invasive bladder cancer subtypes using differential graphical model. BMC Genomics 22, 863 (2021). (Zone II, CAS, IF=4.0)
4. Zixuan Wang, Xiaoyao Tan, Beichen Li, Yuhang Liu, Qi Shao, Zijing Li, Yihan Yang, Yongqing Zhang*, BindTransNet: A Transferable Transformer-Based Architecture for Cross-Cell Type DNA-Protein Binding Sites Prediction. In: Wei Y., Li M., Skums P., Cai Z. (eds) Bioinformatics Research and Applications. ISBRA 2021. (CCF Class C meeting)
5. Yongqing Zhang, Siyu Chen, Wenfeng Cao, Peng Guo, Dongrui Gao, Manqing Wang, Jiliu Zhou, Ting Wang *, MFFNet: Multi dimensional Feature Fusion Network based on attraction mechanism for sEMG analysis to detect multiple facade, Expert Systems with Applications, Volume 185, 2021, 115639
6. Yongqing Zhang, Zixuan Wang, Yuanqi Zeng, Jiliu Zhou, Quan Zou *, High resolution transfer factor binding sites prediction improved performance and interpretability by deep learning method, Briefings in Bioinformatics, Volume 22, Issue 6, 2021, bbab273
7. Yongqing Zhang, Shaojie Qiao *, Yuanqi Zeng, Dongrui Gao, Nan Han, Jiliu Zhou, CAE-CNN: Predicting transfer factor binding site with revolutionary autoencoder and revolutionary neural network, Expert Systems with Applications, Volume 1832021115404. (District I, Chinese Academy of Sciences, IF=7.0)
8. Jiaxin Xie, Siyu Chen, Yongqing Zhang, Dongrui Gao and Tiejun Liu *, Combining generative adaptive networks and multi output CNN for motor image classification, Journal of Neural Engineering, Volume 18, Number 42021
9. 郜东瑞，周晖，林志宇，冯李逍，张云霞，彭茂琴，张永清*，基于特征融合和粒子群优化算法的运动想象脑电识别方法，电子科技大学学报，2021,50(3):467-475. (EI期刊)
10. Yongqing Zhang, Qingyuan Chen, Dongrui Gao, and Quan Zou*, GRRFNet: Guided Regularized Random Forest-based Gene Regulatory Network Inference Using Data Integration, IEEE BIBM 2020, 132-139.(CCF Class B meeting)
11. 张永清、卢荣钊、乔少杰*，周激流，一种基于样本空间的类别不平衡数据采样方法，自动化学报，2020(46)11. （CCF T1类期刊）
12. Yongqing Zhang, Yanjiang Rong, Siyu Chen, Meiqin Gong, Dongrui Gao, Min Zhu *, Wei Gan, A Review on the Application of Deep Learning in Bioinformatics, Current Bioinformatics, 2020:15 (8), 898-911
13. Yongqing Zhang, Shaojie Qiao*, Rongzhao Lu, Nan Han, Dingxiang Liu, Jiliu Zhou, “How to balance the bioinformatics data: pseudo-negative sampling”, BMC Bioinformatics. 20 (S25). (Zone 3, Chinese Academy of Sciences, IF=3.2)
14. Yongqing Zhang, Shaojie Qiao*, Shengjie Ji, Yizhou Li, “DeepSite: Bidirectional LSTM and CNN Models for Predicting DNA-protein Binding”, International Journal of Machine Learning and Cybernetics. 11, 841-851(2020). (Zone 3, CAS, IF=4.0)
15. Yuanqi Zeng, Meiqin Gong, Meng Lin, Dongrui Gao, Yongqing Zhang *, A Review about Translation Factor Binding Sites Prediction Based on Deep Learning, IEEE ACCESS, 2020 (8): 219256-219274
16. Yongqing Zhang, Shaojie Qiao *, Shengjie Ji, Nan Han, Dingxiang Liu, Jialiu Zhou, "Identification of DNA Protein Binding Sites by Bootstrap Multiple Collaborative Neural Networks", Engineering Applications of Artistic Intelligence, Volume 79, March 2019, Pages 58-66. (District II, CAS, IF=6.2)
17. Zhang, Yongqing; Cao, Xiaoyi; Zhong, Sheng *, "GeNemo: a search engine for web based functional genomic data", Nuclear Acids Research, 20 April, 2016, 44, W122-127