My primary research focuses on the development of novel statistical methodology for the analysis of high dimensional data, including linear mixed models (LMM), low-rank approximation, and interaction detection in high dimensional regression. I am also interested in the applications of statistical methods in genomics data analysis and pattern recognition. My research papers have appeared in high impact journals, such as The American Journal of Human Genetics, IEEE Transactions on Pattern Analysis and Machine Intelligence, Bioinformatics.
- C. Yang, L. Wan, S. Zhang and H. Zhao. Accounting for Non-Genetic Factors by Low-Rank Representation and Sparse Regression for eQTL Mapping. Bioinformatics. 2013.
- X. Zhou, C. Yang and W. Yu. Moving objects segmentation by detecting contiguous outlier in low-rank representation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 35(3): 597-610, 2013.
- C. Yang, X. Zhou, X. Wan, Q. Yang, H. Xue and W. Yu. Identifying disease-associated SNP clusters via contiguous outlier detection, Bioinformatics, 27(18): 2578-2585, 2011.
- X. Wan*, C. Yang*, Q. Yang, H. Xue, X. Fan, N. Tang and W. Yu. BOOST: a fast approach to detecting gene-gene interactions in genome-wide case-control studies. The American Journal of Human Genetics, 87(3):325-340, 2010. *Joint first author.
- C. Yang, Z. He, X. Wan, Q. Yang, H. Xue and W. Yu. SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies. Bioinformatics, 25(4):504-511, 2009.