AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Results indicate that combining protein language models with sequence modeling and class-imbalance learning strategies is an effective way to improve peptide hormone prediction and to improve the recognition of hormone peptides as the minority class.
Recent progress in predicting RNA modification site-disease associations is summarized, with a focus on common modifications such as m6A, m1A, and m7G, and key challenges in this field are highlighted.
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