Robert Nadon
Associate Professor, Department of Human Genetics
![Robert Nadon Robert Nadon](https://www.mcgill.ca/sbms/files/sbms/styles/medium_focal__220_x_220_/public/robert_nadon.jpg?itok=dufAb976)
Robert Nadon began his career as an experimental psychologist and transitioned to statistical analysis of high-throughput biology in the 1990s as Director of Informatics at Imaging Research (in St. Catharines, Ontario). While there, he led a team of statisticians, programmers, and biologists to develop novel statistical algorithms and software for microarray analysis. Among the first to champion currently broadly-accepted formal statistical procedures for gene expression microarrays, he developed the first commercially available software package for analysis of microarray data (ArrayStat). More recently, he conceived and spearheaded the development of the popular FlexArray software package.
Since joining McGill faculty in 2002, Dr. Nadon has given over 50 invited scientific presentations and workshops on high-throughput data analysis. He has been PI on three Génome Québec funded grants on high-throughput methods in genomics and a grant on high-throughput screening funded by FQRNT. He is currently an Associate Editor with BMC Bioinformatics and a panel member on the NSERC Genes, Cells and Molecules Evaluation Group. He has established ties and has forged collaborations with colleagues in France; he was a visiting researcher at the Commissariat à l’Énergie Atomique (CEA) in Grenoble, France (2009-2010) and took the McGill lead toward establishing formal links between McGill and l’Université de la Méditerranée in Marseille. He has consulted internationally for biotechnology and pharmaceutical companies at all stages of research projects for both traditional and high-throughput research studies, from initial concept to final data analysis. A recurrent consultation task is to determine and correct underlying causes of underperformance for ongoing research programs.
My research interests are (1) in developing statistical methods for biotechnology data and (2) developing and advocating good study design and statistical analysis practices. To date, my trainees and I have developed or are developing methods for microarray gene expression, high-throughput screening, image-based high content screening, metabolomics, RNAi and CRISPR, and genome-wide polysomal profiling.