Meta-TGLink: Structure-Enhanced Graph Meta Learning for Few-Shot Gene Regulatory Network Inference

Meta-TGLink is a novel structure-enhanced graph meta-learning framework designed for few-shot gene regulatory network (GRN) inference. By integrating prior biological network structures with meta-learning paradigms, our method enables rapid adaptation to new regulatory contexts with limited labeled data, advancing the robustness and generalizability of GRN prediction in low-data regimes.