Modeling genetic networks and metabolic networks is an important topic in bioinformatics. We propose a qualitative network model which is a combination of the Boolean network and qualitative reasoning, where qualitative reasoning is a kind of reasoning method well-studied in Artificial Intelligence. We also present algorithms for inferring qualitative networks from time series data and an algorithm for inferring S-systems (synergistic and saturable systems) from time series data, where S-systems are based on a particular kind of nonlinear differential equation and have been applied to the analysis of various biological systems.