Preprint
Jul 2026
CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion
This work reformulates GRN inference as an inductive, ranking-centric graph completion problem and introduces the Benchmark, a new benchmark that incorporates an inductive gene-holdout split together with knowledge graph completion metrics to better evaluate top-ranked predictions.
Jiaze Song, Runhao Zhao, Minghao Xu et al.
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