The Wnt/β-catenin signaling pathway is involved in human neural progenitor cell differentiation. This dissertation employs the cyclic workflow of computational systems biology to investigate the pathway spatio-temporal dynamics during differentiation. Quantitative in vitro analyses show biphasic kinetics of the pathway proteins. A computational model is developed to investigate in silico these kinetics in correlation with cell cycle and self-induced signaling. We show the importance of stochastic approach and suggest further experiments, hence closing the computational systems biology loop.