Stem cell differentiation is governed by extracellular signals that activate intracellular networks (or pathways) to drive phenotypic specification. Using a novel gene clustering strategy we determined pathway relationships from a genome-wide transcriptional dataset of skeletal myoblast differentiation. Established myogenic pathways, including cell contractility and cell-cycle arrest, were predicted with extreme statistical significance (p approximately 0). In addition, gene sets associated with angiogenesis, neuronal activity, and mRNA splicing were regulated, exposing developmental and therapeutic implications. Acquisition of transcriptional data spanning the entire differentiation time course provided context for a dynamic landscape of functional pathway regulation. This novel perspective on myogenic cell differentiation revealed previously unrecognized patterns of regulation. We predict that similar analyses will facilitate ongoing efforts to define molecular mechanisms in other stem cell and developmental paradigms. Finally, by combining an iterative process of analysis with supplementation of novel pathways, this application may evolve into a powerful discovery tool.