31/05 - Kateryna Makova: Explaining and predicting disease occurrence from omics data

With advances in current technologies, we can now generate genomics, microbiomics, metabolomics, and epigenomics data, which may help us understand the patterns of disease occurrence. As an example, I will present various omics datasets related to childhood obesity. I will also discuss applications of Functional Data Analysis, a statistical method, to the analysis of these omics data.

A native of Ukraine, Kateryna Makova received her PhD from Texas Tech University, where she studied the genetic consequences of the Chernobyl Nuclear Power Plant accident. She then completed her postdoctoral studies at the University of Chicago, where she investigated differences in mutation rates between males and females, among other topics.

She has been a Professor in the Department of Biology at the Pennsylvania State University since 2003. Her laboratory conducts research in evolutionary and medical genomics. Current topics of interest include sex chromosome evolution, evolution of non-B DNA, mitochondrial DNA evolution, regional variation in mutation rates, and childhood obesity. The research in Dr Makova’s laboratory is highly interdisciplinary and collaborative. The group collaborates with statisticians, computer scientists, and biochemists.