Dr. Mohamad Saad

Scientist

Data Analytics

msaad@hbku.edu.qa

Research Focus at QCRI

Dr. Mohamad Saad’s research encompasses topics including statistical genetics, biostatistics, bioinformatics, systems biology and genetics. 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, Alzheimer’s disease and cancer. These approaches aim to discover new genetic and environmental causes for those diseases in order to find cures, prevention measures and better therapies.

His research expertise includes many analytical approaches that are being used and proposed for Genome Wide Association Studies (GWAS) such as: 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.

Previous Experience

Dr. Mohamad Saad is a 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, bioinformatics, and systems biology.

Dr. Saad has a background in applied mathematics and statistics. He obtained his Bachelor's degree in Applied Mathematics (Majoring in Statistics) at Lebanese University in 2006, before he moved to France where he obtained his Masters degree in Statistics/Biostatistics from the University of Montpellier II, Monpellier in 2007, and his Ph.D. in Statistical Genetics/Biostatistics/Bioinformatics from University of Paul Sabatier III, Toulouse, in 2012.

In Summer 2012, he moved to the United States for a postdoctoral position and joined the Department of Biostatistics at the University of Washington, Seattle, as a Postdoctoral Senior Fellow and stayed until Fall 2016.

Education

2012: Ph.D. in Statistical Genetics / Biostatistics, University of Paul Sabatier 111 & National Institute of Health and Medical Research, Toulouse, France

2007: M.Sc. in Statistics/Biostatistics, Montpellier University, France

2006: B.Sc. in Applied Mathematics (Majoring in Statistics), Beirut, Lebanon

Selected Research

Kunji K, Ullah E, Nato AQ, Wijsman EM, Saad M, GIGI-Quick: A Fast Approach to Impute Missing Genotypes in Genome-Wide Association Family Data, Bioinformatics, 2017

Saad M and Wijsman EM, Association score testing for rare variants and binary traits in family data with shared controls, Briefings in Bioinformatics, 2017

Saad M and Wijsman EM, Combining family- and population-based imputation data for association analysis of rare and common variants in large pedigrees. Genet Epidemiol, 38(7):579-90, 2014

Nalls MA, Pankratz N, Lill C, Chuong B Do, Dena G. Hernandez, Saad M, […], Singleton AB. Large Scale Meta Analysis of Genome-wide Association Data in Parkinson’s Disease Reveals 28 Distinct Risk Loci. Nature Genetics, 46(9):989-93 2014

Nalls MA, Plagnol V, Hernandez DG, Sharma M, Sheerin UM, Saad M, [...], Singleton AB, Wood NW, Imputation of sequence variants for identification of genetic risks for Parkinson's disease: a meta-analysis of genome-wide association studies, The Lancet, 377 (9766), 641-649

Kim S, Saad M, Tsuang DW, Wijsman EM. Visualization of Haplotype Sharing Patterns in Pedigree Samples. Hum Hered, 78(1):1-84, 2014

Saad M and Wijsman EM, Power of Family-Based Association Designs To Detect Rare Variants in Large Pedigrees Using Imputed Genotypes. Genet Epidemiol, 38(1):1-9 2013

Nalls MA, Saad M, Noyce AJ, Keller MF, Schrag A, Bestwick JP, Traynor BJ, Gibbs JR, Hernandez DG, Cookson MR and others. Genetic comorbidities in Parkinson’s disease. Hum Mol Genet, 1 ;23(3):831-41, 2013

Saad M, Lesage S, Saint-Pierre A, [...], Martinez M and Brice A, Genome-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

For other research see his Google Scholar page

Professional Associations and Awards

2014: James V. Neel Young Investigator Award for the Best Presentation by a Young Investigator at the International Genetic Epidemiology Society, Vienna, Austria, August 2014.