个人简介
於东军, 男, 工学博士, 南京理工大学计算机科学与工程学院智能科学与技术系教授, 博士生导师。主要研究方向为生物信息计算、机器学习、模式识别与智能系统。主持及参与多项国家自然科学基金及省部级项目，在模式识别、生物信息学、神经网络、智能计算等领域有一定的研究积累，累计发表学术论文80余篇，主编21世纪高校应用型规划教材《Java程序设计与应用开发》(2009)。近年来主要从事生物信息及模式识别领域相关的课题研究，相关成果已发表在Bioinformatics、Journal of Chemical Information and Modeling、Pattern Recognition、Machine Learning、IEEE/ACM Transactions on Computational Biology and Bioinformatics、IEEE Transactions on NanoBioscience、Journal of Computational Chemistry、BMC Bioinformatics、Amino Acids、计算机学报、计算机研究与发展、软件学报等国内外刊物上。曾获江苏省科技进步三等奖(2001)、江苏省优秀硕士论文(2002)、南京理工大学董事会奖教金一等奖 (2007)、教育部科技进步(推广类)二等奖(2009)以及教育部科技进步二等奖(2012)。入选江苏省博士集聚计划(2013)、江苏省“333高层次人才培养工程”中青年科学技术带头人(2013)、江苏省“六大人才高峰”(2013)以及南京理工大学“科技工作先进个人”(2014)。英国The University of York计算机系访问学者(2008)，美国The University of Michigan (Ann Arbor)计算医学与生物信息学系访问学者(2016)。
近期论文
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Yi-Heng Zhu, Jun Hu, Xiaoning Song, and Dong-Jun Yu*. DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembling Hyperplane-Distance-based Support Vector Machines [J]. Journal of Chemical Information and Modeling. 2019, 59 (6): 3057-3071.
Yang Li, Jun Hu, Chengxin Zhang, Dong-Jun Yu*, and Yang Zhang*. ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks [J]. Bioinformatics, 2019, In Press.
Yanchao Li, Yong li Wang, Dong-Jun Yu, Ye Ning, Peng Hu, and Ruxin Zhao. ASCENT: Active Supervision for Semi-supervised Learning [J]. IEEE Transactions on Knowledge and Data Engineering, 2019, In Press.
Yang Li, Chengxin Zhang, Eric W. Bell, Dong-Jun Yu*, Yang Zhang*, Ensembling multiple raw coevolutionary features with deep residual neural networks for contact-map prediction in CASP13, Proteins, 2019, In Press.
Jun Hu, Xiao-Gen Zhou, Yi-Heng Zhu, Dong-Jun Yu*, and Gui-Jun Zhang*. TargetDBP: Accurate DNA-Binding Protein Prediction via Sequence-based Multi-View Feature Learning [J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2019, In Press.
Yi-Heng Zhu, Jun Hu, Yong Qi, and Dong-Jun Yu*. Boosting Granular Support Vector Machines for the Accurate Prediction of Protein-Nucleotide Binding Sites. Combinatorial Chemistry & High Throughput Screening, 2019, In Press.
Xiao-Rong Bao, Yi-Heng Zhua, and Dong-Jun Yu*. DeepTF: Accurate Prediction of Transcription Factor Binding Sites from DNA Sequence by Combining Multi-Scale Convolutional Neural Network and Long Short-Term Memory Neural Network. IScIDE, 2019, In Press.
Xiaoning Song, Guosheng Hu, Jian-Hao Luo, Zhenhua Feng, Dong-Jun Yu, and Xiao-Jun Wu. Fast SRC using Quadratic Optimisation in Downsized Coefficient Solution Subspace [J]. Signal Processing. 2019, 161: 101-110.
He Yan, Qiao-Lin Ye, and Dong-Jun Yu*. Efficient and robust TWSVM classification via a minimum L1-norm distance metric criterion [J]. Machine Learning, 2019, 108 (6): 993–1018.
於东军, 李阳. 蛋白质残基接触图预测综述 [J]. 南京理工大学学报: 自然科学版, 2019, 43 (1): 1-12.
Muhammad Kabir, Muhammad Arif, Farman Ali, Saeed Ahmad, Zar Nawab Khan Swati, and Dong-Jun Yu*. Prediction of membrane protein types by exploring local discriminative information from evolutionary profiles [J]. Analytical Biochemistry, 2019, 564: 123-132.
Jingzheng Li, Xibei Yang, Xiaoning Song, Jinghai Li, Pingxin Wang, and Dong-Jun Yu. Neighborhood attribute reduction: A multi-criterion approach. International Journal of Machine Learning and Cybernetics. 2019, 10 (4): 731-742.
於东军, 朱一亨, 胡俊. 识别蛋白质配体绑定残基的生物计算方法综述 [J]. 数据采集与处理, 2018, 33 (2): 195-206.
Jun Hu, Zi Liu, Dong-Jun Yu*, and Yang Zhang*. LS-align: an atom-level, flexible ligand structural alignment algorithm for efficient virtual screening [J]. Bioinformatics, 2018, 34 (13): 2209-2218.
Muhammad Kabir, Muhammad Arif, Saeed Ahmad, Zakir Ali, and Dong-Jun Yu*. Intelligent computational method for discrimination of anticancer peptides by incorporating sequential and evolutionary profiles information [J]. Chemometrics and Intelligent Laboratory Systems. 2018, 182: 158-165.
Farman Ali, Muhammad Kabir, Muhammad Arif, Zar Nawab Khan Swati, Zaheer Ullah Khan, Matee Ullah, and Dong-Jun Yu*. DBPPred-PDSD: Machine Learning Approach for Prediction of DNA-binding Proteins using Discrete Wavelet Transform and Optimized Integrated Features Space [J]. Chemometrics and Intelligent Laboratory Systems. 2018, 182: 21-30.
Ming Zhang, Yan Xu, Lei Li, Zi Liu, Xibei Yang, Dong-Jun Yu*. Accurate RNA 5-methylcytosine Site Prediction Based on Heuristic Physical-Chemical Properties Reduction and Classifier Ensemble [J]. Analytical Biochemistry, 2018, 550: 41-48.
Jun Hu, Yang Li, Yang Zhang *, and Dong-Jun Yu*. ATPbind: accurate protein-ATP binding site prediction by combining sequence-profiling and structure-based comparisons [J]. Journal of Chemical Information and Modeling. 2018, 58 (2): 501-510.
Muhammad Kabir, Saeed Ahmed, Muhammad Iqbal, Zar Nawab Khan Swati, Liu Zi, and Dong-Jun Yu*. Improving prediction of extracellular matrix proteins using evolutionary information via a grey system model and asymmetric under-sampling technique [J]. Chemometrics and Intelligent Laboratory Systems. 2018, 174: 22-32.
Chun-Qiu Xia, Ke Han, Yong Qi, Yang Zhang, and Dong-Jun Yu*. A Self-Training Subspace Clustering Algorithm under Low-Rank Representation for Cancer Classification on Gene Expression Data [J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2018, 15 (4): 1315-1324.
He Yan, Qiaolin Ye, Tianan Zhang, Dong-Jun Yu, et al. Least squares twin bounded support vector machines based on L1-norm distance metric for classification [J]. Pattern Recognition, 2018, 74: 434-447.
He Yan, Qiaolin Ye, Tianan Zhang, Dong-Jun Yu, et al.L1-Norm GEPSVM Classifier Based on an Effective Iterative Algorithm for Classification [J]. Neural Processing Letters, 2018, 48: 273-298.
He Yan, Qiaolin Ye, Tian’an Zhang, and Dong-Jun Yu*. Efficient and robust TWSVM classifier based on L1-norm distance metric for pattern classification. The 4th Asian Conference on Pattern Recognition (ACPR 2017). 2017: 436-441
Jun Hu, Zi Liu, and Dong-Jun Yu*. Enhancing Protein-ATP and Protein-ADP Binding Sites Prediction Using Supervised Instance-Transfer Learning. The 4th Asian Conference on Pattern Recognition (ACPR 2017). 2017: 759-763
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