Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.
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High performance, zero-allocation, low memory usage (8 bytes), low precision (17 digits), partially compatible with int64 and shopspring Decimal
GNN-based gene-selection deep learning model for drug response prediction
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