Inverse Bifurcation Analysis in Gene Systems
Author Information
Author(s): Lu James, Engl Heinz W, Schuster Peter
Primary Institution: Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences
Hypothesis
Can inverse bifurcation problems be formulated as optimization problems to engineer biological networks?
Conclusion
The study demonstrates that inverse bifurcation problems can be effectively solved using optimization techniques to engineer desired behaviors in gene systems.
Supporting Evidence
- The study shows that certain inverse bifurcation problems can be formulated as optimization problems.
- Applications include maximizing regions of qualitative behavior and reverse engineering bistable gene switches.
- The methodology allows for efficient solutions using existing numerical bifurcation software.
Takeaway
This study shows how scientists can use math to figure out how to change gene systems to make them behave in certain ways, like switching on and off.
Methodology
The study formulates inverse bifurcation problems as constrained optimization problems and uses gradient-based optimization algorithms combined with one-parameter continuation methods.
Limitations
The current implementation is suitable for problems involving tens of variables and parameters but may not handle higher dimensionality well.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website