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Explainable Graph Neural Networks for Transparent Target Prioritization

Ai Drug Repurposing

Graph Neural Networks Drug Target Prediction

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Ai Drug Repurposing › Graph Neural Networks Drug Target Prediction

Explainable Graph Neural Networks for Transparent Target Prioritization

This research creates interpretable graph neural network architectures that decompose drug repurposing predictions into human-readable molecular substructures and biological pathways contributing to target selection. The work establishes scientific credibility for computational predictions through mechanistic transparency valued by pharmaceutical researchers.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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