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Molecular Similarity Metrics from SMILES Embeddings for Repurposing Prediction

Ai Drug Repurposing

SMILES-Based Drug Representation Learning

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Ai Drug Repurposing › SMILES-Based Drug Representation Learning

Molecular Similarity Metrics from SMILES Embeddings for Repurposing Prediction

This investigation designs novel distance metrics in SMILES embedding spaces that better capture functional and structural drug similarity relevant to disease targets. The metrics enable more accurate neighbor-based repurposing predictions by reflecting true pharmacological relatedness.

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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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