Games: An ODE Model Development Workflow for Systematic Characterization of Synthetic Genetic Parts

Mathematical modeling is invaluable for advancing our understanding and design of synthetic biological systems. However, the model development process is complicated and often unintuitive, requiring iteration on various computational tasks and comparisons with experimental data. Moreover, ad hoc model development can lead to models that lack objectivity and reproducibility. To help practitioners manage these challenges, we introduce GAMES: a workflow for Generation and Analysis of Models for Exploring Synthetic systems that includes a combination of both automated and human-in-the-loop processes. We systematically consider the process of developing models, including model formulation, parameter estimation, parameter identifiability analysis, experimental design, model reduction, model refinement, and model selection. We demonstrate the workflow with a case study on a chemically responsive transcription factor. The generalizable workflow presented here can enable biologists to more readily build and analyze models for a variety of applications.