Signal transduction is thought to control flexible cellular responses by combining a specific robust response with a regulatory ability to interact with multiple signals. Previous biophysical studies have proposed that cell behavior be expressed in a multidimensional space with a basin of attractors. Alternatively, flow cytometry analysis provides mean fluorescence intensity（ MFI） and coefficient of variation （CV） in an arbitrary cell population. In terms of the biophysical concept, MFI and CV are considered to be the activation energy and cell fluctuations, respectively. In the current study, we present a new approach to understand cell signaling pathways associated with cell behavior linking the above concepts. To link the biophysical concept and flow cytometry data, we measured the phosphorylation levels of signal transducers in a cell and the fluctuation of the phosphorylation level in a population of cells. Topologically, the changes in MFI and CV were categorized into five patterns,which indicated emergent properties of cell behavior. The novel classification method is a simple and effective approach for classifying unknown network systems without using machine learning algorithms or ontology analysis
武田 et al. (Tue,) studied this question.