Not only have these computational methods provided useful insights into human evolution but also have been applied to prioritize causal variants associated with human genetic disorders. As ClassInfo is a service offered to the entire University community, we. I have developed multiple machine learning and statistical frameworks to identify the signatures of deleterious variants from population and functional genomic data. If you would like help in doing this, please contact your Department Administrator. My research is motivated by the insight that evolution operates like a high-throughput mutagenesis experiments: deleterious mutations are quickly purged from populations due to natural selection, which in turn leaves detectable marks on human genomic sequences. I am interested in addressing the problem of “variant of uncertain significance” by unifying evolutionary biology and machine learning. Phone: 97 Email: Location: Center for Environmental & Life Sciences. Therefore, many genetic variants in patients’ genomes are marked as “variant of uncertain significance”, forming a major hurdle for both basic research and medical practice. Assistant Professor, Earth and Environmental Studies. However, it is very challenging to distinguish important variants from neutral ones. Understanding the functional, clinical, and evolutionary significance of genetic variants has become a central question in biology and precision medicine. Research Focuses: Millions of genetic variants have been identified in human genomes and the catalog of genetic variation is still expanding rapidly due to the continual drop of sequencing costs.
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