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In this presentation, Dr. Hart will provide an overview of the various missense prediction algorithms, what they predict, and what biases they reflect. Using functional experimental data as a ground truth, he will describe how his team has 1) assessed algorithm performance using default thresholds, 2) improved the accuracy of existing models, and 3) is continuing to derive new methods with even higher accuracy.