Iryna V Lobach
Division of Biostatistics
New York University, School of Medicine, USA
The primary methodological research of Dr. Lobach is motivated by the problems arising in the areas of genetic and nutrition epidemiology. The special focus is on developing statistical and computational methods for association analysis of complex diseases, such as cancer, hypertension, diabetes. Several challenges arise. One is that complex diseases are caused by both genetic and environmental factors, as well as their interaction. Further, environmental factors, such as nutrient intake, are subject to massive amounts of measurement error. Additionally, genome-wide scans are increasingly used for associating genetic polymorphisms with risk of complex diseases. These studies include large arrays of candidate genes and hence it is critical to develop efficient computational techniques for analysis of such studies with ability to incorporate prior biological information.
Statistical Methodology:
Case-Control Studies of Gene-Environment Interactions; Es-Interests timation based on Pseudo-likelihood; Fine Genotype Mapping; Genome-Wide Association Studies; Haplotype-based Analysis; Markov Chain Monte Carlo Algorithms; Measurement Error Modeling; Pathway-based Analysis; Seemingly Unrelated Regression; Semiparametric Methods.
Applied Statistics:
Genetic and Nutrition Epidemiology; Biomedical Studies; To develop tools to not only extract the richest information from epidemiological and medical studies, but also utilize that information in complex statistical models to answer important biological questions and guide public health interventions, evaluations, and policies.
Metabolomics:Open Access received 895 citations as per Google Scholar report