1). Phylogenetic methods for microbiome analysis
2). Improving polygenic risk scores
3). Multi-omics cancer detection diagnostics
4). Image biomarkers of disease severity
5). Data mining electronic health records
Our research is driven by the question: How do we optimally apply computational statistics and machine learning to big biological data to produce actionable insights and predictions? Our work on this question involves core research projects, management and analysis of big biological data, and development of new analysis methods and associated algorithms.
Our core research projects fall within four major areas:
Genome Variation - where our published work includes papers on inferring relatedness, whole-genome analysis of human migration, and analysis of genome admixture,
Statistical Genetics - where our published work includes papers on association analysis of phenotypes ranging from molecular (including expression quantitative trait loci (eQTL) and related), to complex diseases (including pedigree analysis, genome-wide association studies (GWAS), and analysis of rare diseases),
Network Discovery - where our published work includes papers on causal modeling and network analysis of mixed genomic data types,
Disease Risk Prediction - where our published work includes papers on behavioral and environmental biomarkers, identification of disease subtypes, polygenic risk scores (PRS), and clinical predictors of cancer risk.
Biography
Professor Mezey received his undergraduate degree from the University of Pennsylvania, his PhD from Yale University, and he has been at Cornell University since 2006 and at Weill Cornell Medicine since 2009. He was awarded lifetime tenure in 2011 and was promoted to Full Professor in 2018 at Cornell in the Department of Biological Statistics and Computational Biology (now the Department of Computational Biology) and to Full Professor at Weill Cornell Medicine in both the Department of Genetic Medicine and in the Institute for Computational Biomedicine.
Distinctions:
Genetics Pre-Doctoral Training Grant - National Institutes of Health
University Fellowship – Yale University
David Phillips Fellowship – United Kingdom
Director of the Graduate Field of Computational Biology (2014-2020)
