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Enzyme functional classification using artificial intelligence
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DOI：10.1016/j.tibtech.2025.03.003.png)
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Abstract
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Recent advances in computational biology, especially deep learning models, have significantly accelerated the discovery and annotation of enzyme functions. Diverse enzyme feature extraction methods and machine learning algorithms have facilitated the development of high-performing computational models for enzyme function classification. Deep neural network architectures, including convolutional neural networks, recurrent neural networks, transformers, and graph neural networks, have revolutionized data-driven approaches in predicting enzyme functions. Artificial intelligence has transformed enzyme function classification, making it more scalable and accurate than ever before.
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