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This paper presents the first unified benchmark for pathway-guided therapy response modeling, evaluating three biologically informed architectures (BINN, GraphPath, PATH) across five cancer cohorts from The Cancer Genome Atlas for multi-label prediction of targeted therapy, radiation therapy, and survival outcomes.
This paper introduces VCR-Agent, a multi-agent framework that enhances large language models for biological research by generating and validating mechanistic explanations using structured formalism and the VC-TRACES dataset. The approach improves factual precision in gene expression prediction through verified mechanistic reasoning in virtual cells.