PhD Thesis Defense: Machine Learning for Drug Discovery - Predicting Molecular Properties with Graph Neural Networks.
PhD Thesis Defense: Machine Learning for Drug Discovery - Predicting Molecular Properties with Graph Neural Networks.
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This research focuses on leveraging graph neural networks (GNNs) to enhance drug discovery by addressing challenges in predicting molecular properties. The study outlines the limitations of current tools and emphasizes the importance of developing accurate predictive models. Methodology involves GNN design, dataset preparation, and comprehensive evaluation. Results reveal improved performance and insights with real-world applications, showcasing the potential for innovation. The research...