Wei (Will) Yang, Ph.D.
Year in Program: Completed, Nov 2013
C. Charles Gu, Ph.D.
Associate Professor of Biostatistics (tenured)
Associate Professor of Genetics
Washington University School of Medicine
(viewable via Windows Media Player
click "open" to play)
Wei Yang’s research work has been focused on the development and applications of advanced methods in genetic analysis of complex diseases. His duties include developing statistical models for high-dimensional genetic factors in genome-wide analysis of complex diseases, especially developing methods to detect interaction effects and methods to combine signals from different types of data; developing algorithms and performing computer simulations; and carrying out data analysis of real world studies of complex diseases.
Yang W, Gu CC, A novel method of adaptive boosting identifies risk variants among large number of noise genetic association signals. Poster presented at IGES, Stevenson, WA, 2012 Oct meeting.
Yang W, Chu J, Gu CC, Analyzing genome-wide SNP interactions using the random forest fishing method. Abstract submitted for ASHG San Francisco, CA, 2012 Nov meeting.
Yang, W. Computational Tools for Genome-wide Analysis of Interactions. Oral Presentation. National Institute of Drug Abuse – Genetics Consortium Winter Meeting, Washington DC, USA, Dec 2012.
Yang, W. (Oral Presentation): Similarity-based test for haplotype association analysis in GWAS and beyond. R25 Fellowship Symposium: Statistical and Computational Innovation in Addiction Genetics, Washington University School of Medicine, Saint Louis, MO, December 2013.
Yang W, Gu CC. Random forest fishing: a novel approach to identifying organic group of risk factors in genome-wide association studies. Eur J Hum Genet. 2014 Feb; 22(2):254-259. Epub 2013 May 22. doi: 10.1038/ejhg.2013.109. PMID: 23695277. PMC3895629.
Yang W, Gu CC. A whole-genome simulator capable of modeling high-order epistasis for complex disease. Genet Epidemiol. 2013 Nov; 37(7):686-694. doi: 10.1002/gepi.21761. Epub 2013 Oct 1. PMID: 24114848.