This month’s Stat Soc NSW talk is being given by our own Jean Yang! And it’s here on campus too. Details are below. Michael --- The Statistical Society of Australia Inc., NSW Branch Monthly Meeting for September Wednesday, 12 September 2012 Meeting Room 214/215, Economics and Business building 6.00pm: refreshments 6.30pm: talk 7.30pm: dinner with speaker (all welcome to join) Dr Jean Yang School of Mathematics and Statistics University of Sydney Statistical issues with quantitative proteomics data Protein quantisation using mass spectrometry is a recent, powerful platform for determining relative protein levels for thousands of proteins simultaneously. In recent years, we have witnessed rapid development in spectrometry technologies; however, the statistical analysis of raw tandem spectra as well as processed data remains a challenging task. In this talk, we will use biological studies to illustrate the statistical challenges associated with analysing data from such a platform and approaches for extracting biological patterns and information. My discussion will focus on two separate aspects. The pre-processing component will examine various preprocessing approaches and describe a new method for enhancing deterministic protein identification from identified peptide sequences. The second component will examine different models for finding differentially expressed proteins and the use of external information (such as gene set and possibly other data) for better biological interpretations. Biography of Dr Jean Yang Dr Yang has a bachelors degree in statistics from the University of Sydney and completed her doctoral studies in the Department of Statistics at the University of California, Berkeley where she worked under the supervision of Terry Speed on the design and analysis of microarray experiments. She relocated back to Sydney 7 years ago and currently an ARC Future Fellow at the School of Mathematics and Statistics, University of Sydney. Her research work has centered on the development of statistical methodology and the application of statistics to problems in genomics, proteomics and biomedical research. In particular, her focus is on developing methods for integrating expression studies and other biological metadata such as miRNA expression, sequence information and clinical data. As a statistician who works in the bioinformatics area, she enjoys research in a collaborative environment, working closely with scientific investigators from diverse backgrounds.