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BiG-Net: A knowledge-guided graph learning framework for protein function and localization prediction
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DOI：10.1016/j.knosys.2026.116778.png)
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Abstract
En 中文
• A hybrid BiGRU–GCN framework for protein sequence-based prediction tasks. • Integrates sequential contextual learning with graph relational aggregation. • Demonstrates competitive performance against pretrained protein language models. • Achieves superior performance on selected benchmark datasets without large-scale pretraining. • Provides a lightweight and generalizable framework for diverse protein prediction tasks.
Keywords:
Artificial intelligence
Protein sequence analysis
Graph convolutional networks (GCNs)
Deep learning
Journal
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IF:
7.6
Papers:
1.2W
Citations:
4.5W
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