Dr. Mohamad Saad is a Research Scientist in the Data Analytics group at Qatar Computing Research Institute. He joined QCRI in February 2017 and works on topics in Statistical Genetics, Biostatistics, and Bioinformatics. Dr. Saad has a background in applied mathematics and statistics. He obtained his bachelor's degree in Applied Mathematics (Majoring in Statistics) at the Lebanese University in 2006, before he moved to France where he obtained his master's degree in Statistics/Biostatistics from the University of Montpellier II, Monpellier in 2007, and his PhD in Statistical Genetics/Biostatistics/Bioinformatics from the University of Paul Sabatier III, Toulouse, in 2012. In Summer 2012, he moved to the United States for a Postdoctoral Senior Fellow position at the Department of Biostatistics at the University of Washington, Seattle, as a Postdoctoral Senior Fellow and stayed until Fall 2016. Dr. Saad has many peer-reviewed articles in top-tier journals including Nature Genetics, The Lancet, and Genome Research.
Dr. Saad’s research focuses on topics topics in Statistical Genetics, Biostatistics, and Bioinformatics. He is interested in developing statistical methods, approaches, and computational tools to help understanding the genetic etiology of complex human diseases such as Parkinson’s disease, Cardiovascular Diseases and Cancer. These approaches aim to discover new genetic and environmental causes for those diseases that hopefully lead cure discovery, prevention measures, and better therapies.
His research expertise includes many analytical approaches that are being used and proposed for Genome Wide Association Studies (GWAS): association analysis for common and rare variants in population- and family-based designs, linear mixed models, clustering methods, mutli-dimension reduction techniques, linkage analysis, imputation of missing genotypes, MCMC and LASSO.
Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
2017 - PresentDepartment of Biostatistics, University of Washington, Seattle, USA.
2012 - 2016Faculty of Medical Sciences, Lebanese University, Beirut, Lebanon.
2014 - PresentUniversity of Paul Sabatier III & National Institute of Health and Medical Research, Toulouse, France.
2009 - 2012Montpellier, France.
2006 - 2007Major in Statistics, Beirut, Lebanon.
2002 - 2006Large Scale Meta Analysis of Genome-wide Association Data in Parkinson’s Disease Reveals 28 Distinct Risk Loci. Nature Genetics, 46(9):989-93
2014Wood NW, Imputation of sequence variants for identification of genetic risks for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet, 377(976, 2011
2011Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees, Genome Research, 125-134, 10.1101/gr.236315.118.
2019GIGI-Quick: a fast approach to impute missing genotypes in genome-wide association family data. Bioinformatics, 1;34(9):1591-1593, 10.1093/bioinformatics/btx782.
2018Association score testing for rare variants and binary traits in family data with shared controls. Briefings in Bioinformatics, 18;20(1):245-253, 10.1093/bib/bbx107.
2017Power of Family-Based Association Designs To Detect Rare Variants in Large Pedigrees Using Imputed Genotypes. Genet Epidemiol, 38(1):1-9.
2013Genome-wide association study confirms BST1 and suggests a locus on 12q24 as the risk loci for Parkinson’s disease in the European population. Hum Mol Genet, 20(3):615-27.
2011Use of Support Vector Machines for disease risk prediction in genome-wide association studies: concerns and opportunities. Human Mutation, 33 (12), 1708-1718.
2012