何飞
东北师范大学
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)