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Multi-model biological and sequence information fusion for gene regulatory network inference from single-cell transcriptomics
Identification of transcription factor–target gene interactions and construction of the gene regulatory networks (GRNs) are essential for understanding the molecular mechanisms underlying transcriptional gene regulation. Large-scale single-cell transcriptomics across different tissues offers unprecedented resolution of...
DDI-MMAF: Multi-modal affine fusion of visual and semantic representations for anticancer drug synergy prediction.
DDI-MMAF is proposed, a lightweight cross-modal framework that avoids using explicit high-dimensional omics profiles as direct model inputs and enables accurate synergy prediction from raw minimalist inputs, offering a practical and efficient computational solution for cost-effective drug combination discovery.