Abstract:

Transfer learning techniques leverage pre-trained models on large-scale protein datasets to initialize neural network architectures for PPI prediction tasks, improving performance and generalization capabilities. Graph neural networks are tailored for modeling complex interactions in PPI networks, capturing topological properties and structural characteristics for more accurate predictions.

Description:

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