InPheRNo is a computational method developed to identify 'phenotype-relevant' transcriptional regulatory networks (TRNs). Unlike many existing methods that reconstruct TRNs independent of phenotypic properties, InPheRNo uses a probabilistic graphical model to analyze gene expression profiles and associated phenotypic scores or labels. This allows it to pinpoint regulatory mechanisms directly related to a phenotypic outcome of interest, such as cancer type-specific regulatory mechanisms. The tool can accurately reconstruct TRNs and identify cancer driver transcription factors, with extensions like InPheRNo-ChIP integrating multimodal data (RNA-seq, ChIP-seq) for more precise GRN inference. It is valuable for understanding gene expression programs in healthy and diseased states and for identifying therapeutic targets.