GRNPred: A Multimodal Graph Transformer with Masked Gene Expression Pretraining for Gene Regulatory Network Inference (opens in new tab)

Gene regulatory network (GRN) inference is a key problem in systems biology that aims to identify transcription factor (TF)-target gene interactions from high-dimensional gene expression data, but it remains challenging due to limited labeled data, class imbalance, and complex nonlinear regulatory relationships. To address this, we propose GRNPred, a multimodal graph transformer framework that integrates gene expression, functional annotations, semantic gene descriptions, regulatory motif pri...