RNA-binding proteins (RBPs) regulate the processing and expression of protein-coding transcripts. The goal of the proposed research is to develop a strategy to determine specific mRNA regulatory factors and elements important for investigating any biological processes. First, we will construct a transcriptome-wide post-transcriptional regulatory map of RBP-mRNA interactions by probabilistic modeling of protein occupancy profiles and RNA sequence data, simultaneously inferring binding locations of numerous of RBPs for a specific experimental condition. Next, we will predict specific RBPs with important regulatory functions in a different experimental setting by applying our model to protein occupancy profiles generated from different cellular conditions. Specifically, we will generate protein occupancy profiles for a human adrenocortical cell line stimulated with the primary physiological regulators of adrenal steroid hormones to examine the production of mineralocorticoids, glucocorticoids, and adrenal androgens. This research proposal necessitates a combined wet/dry approach including the complete cycle of genome-wide predictive modeling and experimental validations. The research in this proposal benefits from the molecular biology and genomics background of the Experienced Researcher combined with the computational modeling expertise of the Host Laboratory. This research has transformative potential for the field by effectively learning specific RBP-mRNA interactions from computational modeling of a single experiment.