The study of biological networks has been central to our understanding of life and its complex, dynamic nature. The elucidation of molecular networks began with the discovery and characterization of key cellular processes including metabolism, response to stimuli and control of gene expression. In the last several decades, genomics has emerged as a foundational pursuit within the life sciences. The size of datasets defined in relation to sequenced genomes has grown faster than exponentially, leading to the need for advanced analytical and computational methods. I present here three studies of large RNA-sequencing-based data sets. First, a study of the steady state transcriptional composition for Drosophila cell lines, tissues, developmental stages and biological perturbations provide a deeper understanding of spatiotemporally-resolved regulation in Drosophila, the first and still central genetic model system. This dataset, at the time of my analysis, was the largest and most complete transcriptional atlas ever composed. It was also the first large strand-specific study of its kind, which presented new opportunities and challenges. Second, a study of the RNA targets of 20 RNA binding proteins provides a map for one layer of post-transcriptional regulation, which contributes to the steady states presented in the first study. Finally, a study of transcriptional responses to the principle developmental hormone in arthropods, ecdysone, across 41 different and physiologically distinct cell lines sheds light on the dynamic, responsive nature of gene-regulatory networks that enable cells to differentiate into the diverse tissues that compose developing and mature organisms. These studies provide foundational knowledge, as well as models for future work in systems biology, as genome-scale studies across larger, more diverse cellular states become increasingly prevalent.