职  称:副教授
研究方向:机器学习、深度学习、计算生物学
办公电话:13674307548
办公地点:传媒西221

个人简历

2003/09-2007/06,吉林大学,计算机科学与技术,学士 2007/09-2010/06,吉林大学,计算机科学与技术(生物信息学),硕士 2010/09-2015/06,吉林大学,计算机科学与技术(生物信息学),博士 2018/11-2021/1,美国密苏里大学,生命科学中心,博士后 2015/08-2022/06,东北师范大学,信息科学与技术学院,讲师 2022/07-至今,东北师范大学,信息科学与技术学院,副教授 主持项目: 1. 国家自然科学基金青年项目, 融合多视角3D深度描述子的靶蛋白-配体复合物活性预测研究,2019/01-2021/12,26万 2. 吉林省自然科学基金, 基于胶囊网络的蛋白对接候选复合物排序研究, 2021/7-2024/6,10万 3. 吉林省教育厅,面向动态蛋白质交互组网络的复合深度学习模型研究,2019/1-2020/12,2.5万 4. 吉林省科技厅优秀青年人才基金项目,具有自适应自学习特性的纹理Gabor深度学习网络研究,2017/01-2018/12,8万 部分代表性论文 (21) Discover the Binding Domain of Transmembrane Proteins Based on Structural Universality,2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM),2021 (20) Identifying Genes and Their Interactions from Pathway Figures and Text in Biomedical Articles,2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM),2021 (19) Machine learning methods in prediction of protein palmitoylation sites: A brief review,CURR PHARM DESIGN,2021 (18) He Fei, Li Jingyi, Wang Rui,Xiaowei Zhao,Ye Han. An Ensemble Deep Learning based Predictor for Simultaneously Identifying Protein Ubiquitylation and SUMOylation Sites. BMC Bioinformatics, 2021, 22(1). (17) Duolin Wang, Dongpeng Liu, JIakang Yuchi, Fei He, Yuexu Jiang, Siteng Cai, Jingyi Li, Dong Xu*. MusiteDeep: a deep-learning based webserver for protein post-translational modification si)Khan S M , He F , Wang D , et al. MU-PseUDeep: A deep learning method for prediction of pseudouriing Sun, Yongbing Chen, Bo Liu, Yanxin Gao, Ye Han, Fei He* and Jinchao Ji*. DeepMRMP: A new predictor for multiple types of RNA modification sites using deep learning. Mathematical Biosciences and Engineering, 2019, 16(6):6231-6241.(SCI) (14) Ji J , Pang W , Li Z , et al. Clustering Mixed Numeric and Categorical Data With Cuckoo Search. IEEE Access, 2020, 8:30988-31003.(SCI) (13)Li, Y. , Pu, F. , Wang, J. , Zhou, Z. , Zhang, C. , & He, F. , et al. (2021). Machine learning methods in prediction of protein palmitoylation sites: a brief review. Current Pharmaceutical Design.(SCI) (12)Lu, C. , Liu, Z. , Zhang, E. , He, F. , & Wang, H. . (2019). Mpls-pred: predicting membrane protein-ligand binding sites using hybrid sequence-based features and ligand-specific models. International Journal of Molecular Sciences, 20(13), 3120.(SCI) (11)Fei He, Rui Wang, Jiagen Li, Lingling Bao, Dong Xu and Xiaowei Zhao. Large-scale prediction of protein ubiquitination sites using a multimodal deep architecture, BMC Systems Biology. 2018, 12(Suppl 6):109 (SCI) (10)Xiaowei Zhao, Jiagen Li, Rui Wang, Fei He, Lin Yue, Minghao Yin. General and Species-Specific Lysine Acetylation Site Prediction Using a Bi-Modal Deep Architecture, IEEE Access. 2018, 6: 63560-63569 (SCI) (9)Ye Han, Fei He, Yongbing Chen, Yuanning Liu and Helong Yu. SiRNA silencing efficacy prediction based on a deep architecture, BMC Genomics 2018,19(Suppl 7):670 (SCI) (8)Fei He, Lingling Bao, Rui Wang, Jiagen li, Dong Xu, Xiaowei Zhao. A multimodal deep architecture for large-scale protein ubiquitylation site prediction, IEEE International Conference on Bioinformatics and Biomedicine. IEEE Computer Society, 2017:108-113(CCF推荐B类会议) (7)Ye Han, Fei He, Xian Tan, Helong Yu. Effective small interfering RNA design based on convolutional neural network, IEEE International Conference on Bioinformatics and Biomedicine. IEEE Computer Society, 2017:16-21(CCF推荐B类会议) (6)Fei He, Ye Han, Jianting Gong, Jiazhi Song, Han Wang, Yanwen Li. Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level, Scientific Reports,2017,7: 44836(SCI) (5)Fei He,Ye Han,Han Wang,Jinchao Ji,Yuanning Liu,Zhiqiang Ma,A Deep Learning Architecture for Iris Recognition based on Optimal Gabor Filters and Deep Belief Network, Journal of Electronic Imaging, 2017, 26(2) : 023005(SCI) (4)Yuanning Liu, Fei He, Xiaodong Zhu, Ying Chen, Yan Han, Yanning Fu. Video Sequence-Based Iris Recognition Inspired by Human Cognition Manner. Journal of Bionic Engineering, 2014, 11(3): 481-489. (导师外第一作者,SCI) (3)Yuanning Liu, Fei He, Xiaodong Zhu, Zhen Liu, Ying Chen, Ye Han, Lijiao Yu. The Improved Characteristics of Bionic Gabor Representations by Combining with SIFT Key-points for iris Recognition. Journal of Bionic Engineering, 2015, 12(3) : 504-517.(导师外第一作者,SCI) (2)Fei He, Yuanning Liu, Xiaodong Zhu, Chun Huang, Ye Han, Hongxing Dong. Multiple localfeature representations and their fusion based on an SVR model for irisrecognition using optimized Gabor filters. EURASIP Journal on Advances in Signal Processing, 2014(1), 95(SCI) (1)Fei He, Yuanning Liu, Xiaodong Zhu, Chun Huang, Ye Han, Ying Chen. Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric. Journal of Electronic Imaging, 2014, 23(3): 033019(SCI)

社会兼职

获奖情况 (数据来源:科学技术处、社会科学处)

教学信息 (数据来源:教务处)

  • 生物信息学(硕士)
  • 生物信息学
  • 项目实践
  • C#.NET程序设计
  • 操作系统
  • 操作系统实验

科研信息 (数据来源:科学技术处、社会科学处)

  • 项目:
  • 1. 基于胶囊网络的蛋白对接候选复合物排序研究,省、市、自治区科技项目,2021年
  • 2. 面向动态蛋白质交互组网络的复合深度学习模型研究,省、市、自治区科技项目,2018年
  • 3. 融合多视角3D深度描述子的靶蛋白-配体复合物活性预测研究,国家自然科学基金项目,2018年
  • 4. 具有自适应自学习特性的纹理Gabor深度学习网络研究,省、市、自治区科技项目,2017年
  • 5. 大规模纹理分类的深度Gabor卷积神经网络构建,自选课题,2016年
  • 论文:
  • 1. THPLM: a sequence-based deep learning framework for protein stability changes prediction upon point variations using pretrained protein language model,BIOINFORMATICS,2023年
  • 2. Deciphering and identifying pan-cancer RAS pathway activation based on graph autoencoder and ClassifierChain,ELECTRONIC RESEARCH ARCHIVE,2023年
  • 3. Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining,Medical Review,2023年
  • 4. Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning,COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,2022年
  • 5. Sampling and ranking spatial transcriptomics data embeddings to identify tissue architecture,FRONTIERS IN GENETICS,2022年
  • 6. Discover the Binding Domain of Transmembrane Proteins Based on Structural Universality,2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM),2021年
  • 7. Identifying Genes and Their Interactions from Pathway Figures and Text in Biomedical Articles,2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM),2021年
  • 8. An Ensemble Deep Learning based Predictor for Simultaneously Identifying Protein Ubiquitylation and SUMOylation Sites,BMC BIOINFORMATICS,2021年
  • 9. Machine learning methods in prediction of protein palmitoylation sites: A brief review,CURR PHARM DESIGN,2021年
  • 10. A multi-view clustering algorithm for mixed numeric and categorical data,IEEE ACCESS,2021年
  • 11. MU-PseUDeep: A deep learning method for prediction of pseudouridine sites,COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL,2020年
  • 12. MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization,NUCLEIC ACIDS RESEARCH,2020年
  • 13. Clustering Mixed Numeric and Categorical Data With Cuckoo Search,IEEE ACCESS,2020年
  • 14. Phenotype prediction and genome-wide association study using deep convolutional neural network of soybean,FRONTIERS IN GENETICS,2019年
  • 15. Protein Ubiquitylation and Sumoylation Site Prediction Based on Ensemble and Transfer Learning,2019 IEEE International Conference on Bioinformatics and Biomedicine(BIBM),2019年
  • 16. DeepMRMP: A new predictor for multiple types of RNA modification sites using deep learning,MATH BIOSCI ENG,2019年
  • 17. MPLs-Pred: Predicting Membrane Protein-Ligand Binding Sites Using Hybrid Sequence-Based Features and Ligand-Specific Models,INT J MOL SCI,2019年
  • 18. Clustering mixed numeric and categorical data with artificial bee colony strategy,J INTELL FUZZY SYST,2019年
  • 19. Understanding Membrane Protein Drug Targets in Computational Perspective,CURR DRUG TARGETS,2019年
  • 20. Large-scale prediction of protein ubiquitination sites using a multimodal deep architecture,BMC SYSTEMS BIOLOGY,2018年
  • 21. General and Species-Specific Lysine Acetylation Site Prediction Using a Bi-Modal Deep Architecture,IEEE ACCESS,2018年
  • 22. 基于模糊质心的混合属性数据模糊加权聚类算法,计算机科学,2018年
  • 23. A Multimodal Deep Architecture for Large-Scale Protein Ubiquitylation Site Prediction,2017 IEEE International Conference on Bioinformatics and Biomedicine(BIBM),2017年
  • 24. Effective small interfering RNA design based on convolutional neural network,2017 IEEE International Conference on Bioinformatics and Biomedicine(BIBM),2017年
  • 25. Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level,SCIENTIFIC REPORTS,2017年
  • 26. Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network,J ELECTRON IMAGING,2017年
  • 27. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity,COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE,2017年
  • 28. Face-iris multimodal biometric scheme based on feature level fusion,J ELECTRON IMAGING,2015年
  • 专利:
  • 多源生物大数据融合系统 2021-08-24
暂停信息维护