NYU Researchers have Created a Neural Network for Genomics that can Explain How it Reaches its Predictions

In the world of biological research, machine-learning models are making significant strides in advancing our understanding of complex processes, with a particular focus on RNA splicing. However, a common limitation of many machine learning models in this field is their lack of interpretability – they can predict outcomes accurately but struggle to explain how they […]

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