S. Stanley Young
S. Stanley Young is the Assistant Director for Bioinformatics.
Dr. Young graduated from North Carolina State University, BS, MES and a Ph.D. in Statistics and Genetics. He worked in the pharmaceutical industry on all phases of pre-clinical research, first at Eli Lilly and then at GlaxoSmithKline. He has authored or co-authored over 50 papers including six “best paper” awards, and a highly cited book, Resampling-Based Multiple Testing. He has two issued patents. He is interested in all aspects of applied statistics, with special interest in chemical and biological informatics. He conducts research in the area of data mining.
Dr. Young is a Fellow of the American Statistical Association and the American Association for the Advancement of Science. He is an adjunct professor of statistics at North Carolina State University, the University of Waterloo and the University of British Columbia where he co-directs thesis work.
Are Medical Articles True on Health, Disease?, GeneticEngineering & Biotechnology News May 1, 2014, Vol. 34, No. 9
Webinar on December 12, 2012 for Society of Toxicology - Risk Assessment Specialty Sections (RASS)
Webinar recording can be accessed here:
"Advancing Statistical Thinking in Observational Health Care Research" by R. L. Obenchain, Risk Benefit Statistics LLC, Carmel, IN 46033, U.S.A., and S. S. Young, National Institute of Statistical Sciences, RTP, NC 27709, U.S.A.
The paper will appear in the Journal of Statistical Theory and Practice in 2013.
This paper illustrates use of the Local Control (LC) approach to estimate Local Treatment Differences (LTDs) in large, observational datasets, and the "mddsim.zip" archive contains the simulated data for 40,000 patients diagnosed with Major Depressive Disorder (MDD) used as the numerical example in this paper.
Poster- Ten-sided Dice Experiment
Click here to read "Deming, data and observational studies. A process out of control and needing fixing", Significance, September 2011
"Everything is Dangerous" lecture.
Click here to watch presentation of "Pre-processing HCS data using Non-negative Matrix Factorization"
Click here to see "Non-Negative Matrix Factorization Materials."
Click here to download PowerMV, chemistry visualization software.
Click here to read Lecture on Comparative Effectiveness Research