Purpose: Describe a high-throughput method for the analysis of uncertain models, e.g. in biological research. Methods: Generalized modeling for conceptual analysis of large classes of models. Results: Local dynamics of uncertain networks are revealed as a function of intuitive parameters. Conclusions: Generalized modeling easily scales to very large networks.Keywords Generalized modeling · high-throughput method · uncertain models · biological research
BackgroundThe ongoing revolution in systems biology is revealing the structure of important systems. For understanding the functioning and failure of these systems, mathematical modeling is instrumental, cp. Table 1. However, application of the traditional modeling paradigm, based on systems of specific equations, faces some principal difficulties in these systems. Insights from modeling are most desirable during the early stages of exploration of a system, so that insights from modeling can feed into experimental set ups.