A transcription factor regulatory atlas for activity inference and perturbation prediction
TFActProfiler is presented, a TF–mRNA resource and computational framework that learns signed, quantitative TF–mRNA regulatory coefficients by integrating heterogeneous prior evidence (ChIP-based, motif-based, and curated TF–mRNA annotations) with large-scale bulk and single-cell RNA-seq atlases.