William Stewart,

I develop statistical methods for researchers who seek quick and efficient analyses of new and computationally challenging data. Consequently, I am interested in developing methods for newly emerging data types that are motivated by scientific discovery (e.g. SNP intensity data of related individuals). Using both family and population based data, I have developed improved methods for mapping genetic risk variants for psychiatric disorder (e.g. genes and CNVs related to Alzheimer's disease and bipolar disorder, respectively), and for estimating genetic maps by combining information efficiently from multiple studies (i.e. meta-analyses). In addition, I have a general interest in deterministic math models, gene networks, and problems that arise in computational molecular biology. Most of my methods employ a rich variety of deterministic and stochastic algorithms, Monte Carlo sampling techniques, and various optimization procedures to estimate genetic quantities of interest (e.g. lod scores, kinships, CNV frequencies and carrier status) in fairly general settings.

Gender:

• Male

Languages Spoken:

• English

Research Center:

• Battelle Center for Mathematical Medicine

Undergraduate School

• San Francisco State University
  Date Completed: 05/01/1999

Master's

• University of Washington
  Date Completed: 05/01/2002

Doctoral

• University of Washington
  Date Completed: 11/01/2005

Post Doctoral

• University of Michigan
  Date Completed: 06/01/2008

2012–present

• Principal Investigator, Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital

• Greenberg DA, Stewart WC. 2012. How should we be searching for genes for common epilepsy? A critique and a prescription.  Epilepsia. Vol. 53, no. September: 4:72-80.
• Stewart,William CL; Subaran, Ryan L. 2012. Obtaining Accurate p Values from a Dense SNP Linkage Scan.  HUMAN HEREDITY. Vol. 74, no. 1. (January): 12-16.
• Stewart WCL, Huang Y, Greenberg DA, Vieland VJ. Next Generation Linkage and Association Methods Applied to Hypertension: A Multi-Faceted Approach to the Analysis of Sequence Data.  BMC Genetics Proceedings.
• Lipner EM, Tomer Y, Noble JA, Monti MC, Lonsdale JT, Corso B, Stewart WCL, Greenberg DA. HLA class I and II alleles are associated with microvascular complications of type 1 diabetes.  Human Immunology.