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Dr. Brett Trost's research program is dedicated to the creation and application of novel computational biology methods for detecting and interpreting genetic variation, particularly in the context of neurodevelopmental and mental health conditions. His main interests include developing new ways to predict the pathogenicity of missense variants and inferring the effects of protein-protein interactions and post-translational modifications. Dr. Trost’s long-term aim is to leverage multi-omic data (e.g., transcriptomics, proteomics, metabolomics, epigenetics) combined with machine-learning approaches to understand disease-associated genetic variation.
Department of Sociology