何飞 - 东北师范大学 - 信息科学与技术学院

个人简介

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 2015/08-，东北师范大学，信息科学与技术学院，讲师 2018/11-2020/11，美国密苏里大学，生命科学中心，博士后

研究领域

研究方向：机器学习、深度学习、计算生物学

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

（1）Pingping 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.(SCI, 通讯作者) （2）Fei He, Duolin Wang, Yulia Innokenteva, Olha Kholod, Dmitriy Shin and Dong Xu. 2019. Extracting Molecular Entity and Their Interactions from Pathway Figures Based on Deep Learning. In Proceedings of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB’19). Niagara Falls, NY, USA（权威会议）（3）Chang Lu, Zhe Liu, Enju Zhang, Fei He, Zhiqiang Ma, Han Wang. MPLs-Pred: Predicting Membrane Protein-Ligand Binding Sites Using Hybrid Sequence-Based Features and Ligand-Specific Models. International Journal of Molecular Sciences.2019. 20(13), 3120.(SCI, 通讯作者) （4）Jijin Ji, Yongbing Chen,Guozhong Feng, Xiaowei Zhao, Fei He. Clustering mixed numeric and categorical data with artificial bee colony strategy.2019, Journal of Intelligent & Fuzzy Systems, 1-10. (SCI, 通讯作者) （5）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) （6）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) （7）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）（9）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）（10）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）（11）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）（12）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）（13）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）（14）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）（15）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）（16）Ye Han, Yuanning Liu, Hao Zhang, Fei He, Chonghe Shu, liyan Dong. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity. Computational & Mathematical Methods in Medicine, 2017, 2017(8):5043984.（SCI）