Email: yangyang AT cs DOT sjtu DOT edu DOT cn
Office: 3#-501 of SEIEE buildings in Minghang campus
She is interested in developing efficient algorithms and software for computational problems in molecular biology and biomedine with machine learning and data ming approaches. In particular, her research includes biological sequence analysis and classification, biomedial image processing, non-coding RNA identification and gene regulatory network construction for complex diseases.
Ph.D. Computer Science (June, 2009), Shanghai Jiao Tong University, Shanghai, P. R. China
Visiting Ph.D. student (2007 - 2009), University of California, Riverside, CA, USA
B.S. Computer Science (June, 2003), Shanghai Jiao Tong University, Shanghai, P. R. China
Assistant and Associate Professor, Dept. of Computer Science, Shanghai Jiao Tong Univ., Shanghai, Jan 2014 - present
Visiting Scholar, Dept. of Computer Science, University of California, Riverside, Oct 2012 - Oct 2013
Assistant and Associate Professor, Dept. of Computer Science, Shanghai Maritime Univ., Shanghai, Jul 2009 - Dec 2013 2012
Machine Learning CS385 (for “IEEE Honored Class”) Spring 2016 – 2019
Algorithms EI334 (for “IEEE Honored Class”) Spring 2014
Advanced Programming Language Design CS902 Autumn 2014
Mathematical Logic MA115 Autumn 2014
l Study on reliable screening of microRNA biomarkers, the Shanghai Municipal Natural Science Foundation (No. 16ZR1448700), 7/2016 - 6/2019.
l Computational prediction of type III secreted effectors from gram-negative bacteria, the National Natural Science Foundation of China (Grant No. 61003093), 1/1/2011 - 12/31/2013.
l Study on the classification of biological sequences? the Science Foundation for The Excellent Youth Scholars of Shanghai Municipality, 7/1 /2010 - 6/30/2012.
l Yang Yang, Qingwei Fang, Hong-Bin Shen, Predicting gene regulatory interactions based on spatial gene expression data and deep learning, PLOS Computational Biology, 2019 (in press).
l Wei Long, Tiange Li, Yang Yang*, Hong-Bin Shen, FlyIT: Drosophila Embryogenesis Image Annotation based on Image Tiling and Convolutional Neural Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019 (in press). (* corresponding author)
l Yang Yang, Mingyu Zhou, Qingwei Fang, Hong-Bin Shen. (2019). Annofly: Annotating drosophila embryonic images based on an attention-enhanced RNN model. Bioinformatics, Volume 35, Issue 16, 15 August 2019, Pages 2834–2842.
l Xiaoyong Pan#, Yang Yang#, Chun-Qiu Xia, Aashiq H. Mirza, and Hong-Bin Shen, Recent Methodology and Progress of Deep learning for RNA-protein interaction prediction. WIREs RNA, 2019:e1544. (# equal contribution)
l Di Wang, Ling Geng, Yu-Jun Zhao, Yang Yang, Yan Huang, Yang Zhang, and Hong-Bin Shen， Artificial intelligence-based multi-objective optimization protocol for protein structure refinement. Bioinformatics, 2019 (in press).
l Shuo Yin, Biao Zhang, Yang Yang, Yan Huang and Hong-Bin Shen, Clustering enhancement of noisy cryo-electron microscopy single-particle images with a network structural similarity metric. Journal of Chemical Information and Modeling, 2019, Volume 59, Issue 4, 1658-1667.
l Yang Yang, Xiaofeng Fu, Wenhao Qu, Yiqun Xiao and Hong-Bin Shen, MiRGOFS: A GO-based functional similarity measure for miRNAs, with applications to the prediction of miRNA subcellular localization and miRNA-disease association, Bioinformatics, Volume 34, Issue 20, 15 October 2018, Pages 3547–3556.
l Hanjin Zhang#, Yang Yang# and Hong-Bin Shen, “Detection of Curvilinear Structure in Images by a Multi-Centered Hough Forest Method,” IEEE Access, 2018, vol 6
l Zhen Cao#, Xiaoyong Pan#, Yang Yang#, Yan Huang and Hong-Bin Shen, “The lncLocator: a subcellular localization predictor for long non-coding RNAs based on a stacked ensemble classifier, Bioinformatics, Volume 34, Issue 13, 1 July 2018, Pages 2185–2194.
l Kaiwen Liu, Yang Yang, Incorporating Link Information in Feature Selection for Identifying Tumor Biomarkers by Using miRNA-mRNA Paired Expression Data, Current Proteomics 15 (2), 165-171
l Xi Yin, Jing Yang, Feng Xiao, Yang Yang, Hong-bin Shen, MemBrain: An easy-to-use online webserver for transmembrane protein structure prediction, Nano-Micro Letters 10 (1), 2.
l Yang Yang, Zhichen Wu and Wei Kong. “Improving clustering of microRNA microarray data by incorporating functional similarity”. Current bioinformatics, 13(1),34-41, 2018
l Hanjin Zhang#, Yang Yang# and Hong-Bin Shen, “Line Junction Detection Without Prior-Delineation of Curvilinear Structure in Biomedical Images,” IEEE Access, 2017, 6：2016-2027
l Yang Yang, Yiqun Xiao, Tianyu Cao and Wei Kong, “MiRFFS: a functional group-based feature selection method for the identification of microRNA biomarkers”, Int. J. Data Mining and Bioinformatics, vol. 18(1), 2017
l W Kong, X Mou, J Deng, B Di, R Zhong, S Wang, Y Yang, W Zeng, Differences of immune disorders between Alzheimer’s disease and breast cancer based on transcriptional regulation, PloS one 12 (7), e0180337, 2017
l Yang Yang, Ning Huang, Luning Hao and Wei Kong, “A clustering-based approach for the identification of microRNA combinatorial biomarkers”, BMC Genomics, 18 (2), 210, 2017
Selected publications before 2017
l Yang Yang*, Zhichen Wu and Wei Kong, ”Improving clustering of microRNA microarray data by incorporating functional similarity”, Current Bioinformatics,2016,11(999)
l Yang Yang*, Zhuangdi Xu and Dandan Song, “Missing value imputation for microRNA expression data by using a GO-based similarity measure”, BMC bioinformatics, 2016,17(1):10
l Wei Kong, Xiaoyang Mou, Jin Deng, Benteng Di, Ruxing Zhong, Shuaiqun Wang, Yang Yang, Weiming Zeng, “Differences of immune disorders between Alzheimer's disease and breast cancer based on transcriptional regulation”, Plos One, 12(7):e0180337
l Wei Kong, Jingmao Zhang, Xiaoyang Mou, Yang Yang, Integrating gene expression and protein interaction data for signaling pathway prediction of Alzheimer’s disease, Computational and Mathematical Methods in Medicine, 2014 , Vol. 3，pp. 340758.
l Wei Kong, Xiaoyang Mou, Xing Zhi, Xin Zhang, Yang Yang，Dynamic regulatory network reconstruction for Alzheimer’s disease based on matrix decomposition techniques, Computational and Mathematical Methods in Medicine, 2014 , Jun. 15, Vol. 6, pp. 891761.
l Wei Kong, Xiaoyang Mou, Na Zhang, Shasha Li, Yang Yang，The construction of common and specific significance subnetworks of Alzheimer’s disease from multiple brain regions , BioMed Research International, 2015
l James Wong, Lei Gao, Yang Yang, Wenbo Ma, et al., “Roles of small RNAs in soybean defense against Phytophthora sojae infection,” The Plant Journal, 2014, doi: 10.1111/tpj.12590
l Yang Yang and Sihui Qi, “A new feature selection method for computational prediction of type III secreted effectors”, International Journal of Data Mining and Bioinformatics, vol. 10, no. 4, 2014.(IF:0.65)
l Bao-liang Lu, Xiaolin Wang, Yang Yang and Hai Zhao, “Learning from imbalanced data sets with a Min-Max modular support vector machine,” Frontiers of Electrical and Electronic Engineering, vol. 6(1), pp. 56-71, 2011
l Yang Yang, Jiayuan Zhao, Robyn L. Morgan, Wenbo Ma, Tao Jiang, “Computational prediction of type III secreted proteins from gram-negative bacteria,” BMC Bioinformatics, 2010, 11(S1):S47
l Yang Yang and Bao-Liang Lu, “Protein subcellular multi-localization prediction using a min-max modular support vector machine,” International Journal of Neural Systems, vol. 20, No. 1, pp. 13-28, 2010.
l Dandan Song#, Yang Yang#, Bin Yu, Binglian Zheng, Zhidong Deng, Bao-Liang Lu, Xuemei Chen and Tao Jiang, “Computational prediction of novel non-coding RNAs in Arabidopsis thaliana”, BMC Bioinformatics 2009, 10(S1):S36
l Conference Publications (Selected)
l Yiqun Xiao, Jiaxun Cai, Yang Yang*, Hai Zhao, and Hongbin Shen, Prediction of MicroRNA Subcellular Localization by Using a Sequence-to-Sequence Model, in Proceedings of the 2018 IEEE International Conference on Data Mining (ICDM'18), Singapore.
l Guowei Ji, Yang Yang*, and Hong-Bin Shen, "IterVM: An Iterative Model for Single-Particle Cryo-EM Image Clustering Based on Variational Autoencoder and Multi-Reference Alignment”, The IEEE International Conference on Bioinformatics and Biomedicine (BIBM’18), Madrid, Spain
l Tiange Li, Yang Yang*, and Hong-Bin Shen,“HMIML: Hierarchical Multi-Instance Multi-Label Learning of Drosophila Embryogenesis Images Using Convolutional Neural Networks” The IEEE International Conference on Bioinformatics and Biomedicine (BIBM’18), Madrid, Spain
l Xiaofeng Fu, Yiqun Xiao, Yang Yang*, “Prediction of Type III Secreted Effectors Based on Word Embeddings for Protein Sequences”, in Proc. International symposium on bioinformatics research and applications, ISBRA 2018
l Yang Yang, Tianyu Cao and Wei Kong, “Feature selection based on functional group structure for microRNA expression data analysis”, the 2016 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2016)