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Á. Sánchez-Pla

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Open access Aug 2026

Self-Attention over Parallel Dense Embeddings for High-Dimensional Omic Data

Results suggest that PLAT provides an effective and interpretable framework for high-dimensional transcriptomic classification and functional enrichment analyses consistently highlighted biological processes and disease pathways associated with breast cancer, supporting the biological relevance of the learned latent representations.

Kamal Elatifi, Nicolas Jäger Gallego, Á. Sánchez-Pla et al. · 0 citations

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