Theoretical models describing complex biological phenomena have been accumulating. However, most of these models have been created with hypothetical parameter determination without seeing actual cell reactions. The parameter determination requires high-dimensional data monitoring, particularly at the protein level. It has been a difficult task to develop the standard model system because of the lack of an appropriate validation technique. Reverse-phase protein lysate microarray (RPA) is one of the most potent technologies for high-dimensional proteomic monitoring. Therefore, proteomic monitoring by RPA may contribute substantially to develop theoretical protein network models based on experimental validation.