Can Yang, PhD

Lecturer in Psychiatry

Research Interests

Data Interpretation, Statistical; Regression Analysis; Models, Statistical; Linear Models; Computational Biology; Genomics

Research Summary

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.

Specialized Terms: High dimensional data analysis´╝îincluding linear mixed models (LMM), low-rank approximation, interaction detection in ultrahigh dimensional regression. Statistical genomics, bioinformatics.

Selected Publications

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Research Image 1

(A) A plot of significant linkage peaks given by standard linear regression (P < 0.01 after Bonferroni correction) for expression QTL in the study (Smith and Kruglyak, 2008) by marker location (x-axis) and expression trait location (y-axis). (B) The plot of linkage peaks in the study (Smith and Kruglyak, 2008) given by our method LORS.

Research Image 2

Moving-objects detection in surveillance videos. More results can be found at

Research Image 3

The main Result from my BOOST paper published in The American Journal of Human Genetics -- Comparison between the Single-Locus Association Mapping and the Interaction Mapping for Type I Diabetes (T1D) and Rheumatoid Arthritis (RA). Top-left panel: Single-locus association mapping of T1D and RA. These two share a very similar hit region in chromosome 6. Top-right panel: The LD map of the MHC region in control samples. Bottom panel: Genome-wide interaction mapping of T1D and RA. 99.8% of T1D interactions and 80.0% of RA interactions are in the MHC region. Strong interaction effects widely exist between genes in and across the MHC class I, II, and III in T1D, whereas most significant interactions of RA involve only loci closely placed in the MHC class II region