A gene network is a network that expresses the activation-inhibition relationship between genes. It is usually modeled with differential equations and analyzed by numerical simulations. However, such approach needs biological parameters, which are often unclear, and thus its applicability is limited. In this study, we consider a gene network as a reactive system (a system that responds appropriately while interacting with the environment) and describe its behavior qualitatively using linear temporal logic. We are studying methods for analyzing whether certain genes can be constantly expressed or oscillate, and whether certain functions are biologically homeostatics.

Process mining is a method that uses data science techniques to find information useful for process improvement, such as business process workflow and relationships between personnel, from execution records (obtained from ERP such as SAP) of business processes. In this research, we are working on issues such as how to extract event logs from business processes, how to find formal models of business processes (models that can be mathematically executed), and how to verify whether business processes satisfy desired properties.