Bioinformatics, Machine Learning and Data Mining

Shanghai Jiao Tong University, Shanghai, P. R. China (2003-2009: PhD)
University of California, Riverside, CA, USA (2007-2009: Visiting PhD student)
Shanghai Jiao Tong University, Shanghai, P. R. China (1999-2003: BS)

Assistant Professor, Dept. of Computer Science, Shanghai Jiao Tong Univ.(2014-)
Research Associate, Dept. of Computer Science, University of California, Riverside (2012-2013)
Assistant & Associate Professor, Dept. of Computer Science, Shanghai Maritime Univ. (2009-2013)

“Study on the approaches for reliably screening microRNA biomarkers”, Shanghai Municipal Natural Science Foundation (No. 16ZR1448700), 2016-2019
“A Study of the transcript and post-transcript co-regulatory network in plant defense response”, Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, 2015-2016
“Identification of tumor metastasis biomarkers for early diagnosis and study on their functional mechanisms”, Start-up Fund of Shanghai Jiao Tong University, 2014-2016
“Computational prediction of type III secreted effectors from gram-negative bacteria”, National Natural Science Foundation of China (No. 61003093), 2011-2013
“Study on the classification of biological sequences”, Science Foundation for The Excellent Youth Scholars of Shanghai Municipality, 2010-2012

Machine Learning (for graduate student)
Machine Learning CS385 (for IEEE Class)

1. Hang Zhou*, Yang Yang*, and Hong-Bin Shen, “Hum-mPLoc 3.0: Prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features,” Bioinformatics, 2016 (*Equal contribution)
2. Yang Yang, Ning Huang, Luning Hao and Wei Kong, “A clustering-based approach for the identification of microRNA combinatorial biomarkers”, BMC Genomics, 2017(IF:3.87)
3. 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):109
4. 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)
5. Yang Yang, Zhichen Wu and Wei Kong, Improving clustering of microRNA microarray data by incorporating functional similarity. Current bioinformatics, 2016.
6. Wei Kong, Xiaoyang Mou, Na Zhang, Weiming Zeng, Shasha Li and Yang Yang, The Construction of Common and Specific Significance Subnetworks of Alzheimer’s Disease from Multiple Brain Regions. BioMed research international, 2015
7. James Wong, Lei Gao, Yang Yang et al. Roles of small RNAs in soybean defense against Phytophthora sojae infection. The Plant Journal, 2014, 79(6):928–940
8. 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, 2014, 10(4):440–454
9. Yang Yang, Identification of novel type III effectors using latent Dirichlet allocation. Computational and mathematical methods in medicine, 2012.
10. Yang Yang, Jiayuan Zhao, Robyn L Morgan, Wenbo Ma and Tao Jiang, Computational prediction of type III secreted proteins from gram-negative bacteria. BMC bioinformatics, 2010, 11(1):1
11. Yang Yang and Bao-Liang Lu, Protein subcellular multi-localization prediction using a min-max modular support vector machine. International Journal of Neural Systems, 2010, 20(01):13–28
12. 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(1):1 (*Equal contribution)