Advancing mutagenicity predictions in drug discovery with an explainable few-shot deep learning framework

Meta-GTMP is a few-shot GNN-Transformer framework that predicts Ames mutagenicity by learning from strain-specific tasks. It integrates graph embeddings and self-attention using a meta-learning strategy to generalize from limited data.

• Publication year

  2025

• Venue

  Digital Discovery

• Publication date

  Unknown publication date

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1039/d5dd00276a
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

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• No concepts are published for this paper.

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