RT Journal Article
SR Electronic
T1 GAMES: A dynamic model development workflow for rigorous characterization of synthetic genetic systems
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.10.20.465216
DO 10.1101/2021.10.20.465216
A1 Kate E. Dray
A1 Joseph J. Muldoon
A1 Niall M. Mangan
A1 Neda Bagheri
A1 Joshua N. Leonard
YR 2021
UL http://biorxiv.org/content/early/2021/12/11/2021.10.20.465216.abstract
AB Mathematical modeling is invaluable for advancing 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. Ad hoc model development can pose a barrier to reproduction and critical analysis of the development process itself, reducing potential impact and inhibiting further model development and collaboration. To help practitioners manage these challenges, we introduce GAMES: a workflow for Generation and Analysis of Models for Exploring Synthetic systems that includes both automated and human-in-the-loop processes. We systematically consider the process of developing dynamic models, including model formulation, parameter estimation, parameter identifiability, 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 in this tutorial can enable biologists to more readily build and analyze models for various applications.Competing Interest StatementThe authors have declared no competing interest.