AUTHOR: Ekaterina Khvatkova
PUBLISHED: July 16th, 2023
MODIFIED: December 31th, 2025
I am a biostatistician in the Department of Biostatistics and Data Science at Wake Forest University School of Medicine (WFUSM). My research interest is in developing and applying statistical association frameworks, mathematical modeling, and integrative functional genomics to investigate the etiopathogenesis of complex diseases. In collaboration with WFUSM principal investigators Carl D. Langefeld and Hannah C. Ainsworth, I am currently investigating a wide range of clinical conditions like autoimmune diseases (e.g., systemic lupus erythematosus, juvenile idiopathic arthritis, uveitis) and neurological disorders (e.g, intracerebral hemorrhagic stroke, Parkinson's disease).
Broadly, modern genetics research involves the use of rapidly-evolving, high-throughput technology to generate large amounts of data from a variety of biological subunits like nucleotides, amino acids, and proteins. The composition and structure of this data depends on the technical methods used to generate it and the intrinsic, interrelated qualities of these subunits. The integrated study of the structure, function, and mapping of collections of these subunits is called “multiomics” in reference to the combination of distinct research angles such as genomics, transcriptomics, proteomics, metabolomics, and epigenomics.
Using techniques in -omic association studies, I am interested in developing and adapting principled quantitative frameworks to understand how these intertwined and context-specific multiomic systems manifest as clinical disorders. Beyond the fundamental scientific study of disease, I am particularly motivated by research questions that prioritize scientific conclusions amenable to clinically tractable and individualized therapeutic strategies.
In my work, I enjoy utilizing my educational background in math, statistics, and the liberal arts by developing multidisciplinary understandings of problems and communicating findings in creative, specialized ways. Outside of connecting data with human context, I believe approaching all aspects of my work with candor and compassion is key to improving the health of individuals and communities.
I plan to post descriptions of several collaborative research projects I work on including more technical descriptions of my involvement in these projects. Stay tuned!