Author

Lisha Zhou

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Open access Jul 2026

A multi-view feature fusion framework with interpretable graph convolution for predicting microbe-drug associations.

IDEAL (Interpretability-Driven Evolvable Attentive Learning for Microbe-Drug Association) is proposed, a multi-view framework that integrates drug network topological attributes, BERT-encoded drug semantics, drug fingerprints, microbe genome sequence attributes, BERT-encoded microbe semantics, and microbe metabolic pathway attributes.

Lisha Zhou · BMC Bioinformatics · 0 citations