Genetics without Bias with Dr. Kiley Graim
Dr. Kiley Graim, assistant professor in the Department of Computer & Information Science & Engineering at the University of Florida, and her lab have developed a new machine learning tool called PhyloFrame, which directly tackles a longstanding challenge in genomics: ancestral bias in genetic data.
Ancestral bias arises when genetic studies disproportionately rely on data from individuals of one ancestry (most often of European descent). This leads to imbalanced insights and ultimately limits the effectiveness of medical advances for individuals from underrepresented backgrounds.
With support from the National Institutes of Health, Dr. Graim and her team demonstrated that PhyloFrame significantly improves how genetic risks are predicted across populations, a crucial step toward equitable precision medicine.
Dr. Graim’s research sits at the powerful intersection of computer science and biology. Her lab develops machine learning models that integrate large-scale genomic datasets to address fundamental questions in health and disease. From mapping the complex networks that underlie human biology to enabling the discovery of personalized therapies, her work pushes the boundaries of how we understand and treat illness.