Dr.
Yang Yang 杨旸
Associate
Professor of the Dept. Computer Science and Engineering
Shanghai
Jiaotong University
No.800
Dongchuan Road, 200240, Shanghai, China
Contact information
Email: yangyang AT cs DOT sjtu DOT edu DOT cn
Office: 3#-501 of SEIEE buildings in Minghang campus
Research
Interests:
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.
Educational Background:
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
Employment History:
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
Teaching
Assignments
Machine Learning (for graduate students) Spring 2015 – 2019
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
Research Grants:
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.
Publications:
Journal
Publications:
2019
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.
2018
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
2017
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)