Optimal Constrained Stationary Intervention in Gene Regulatory Networks
Author Information
Author(s): Babak Faryabi, Golnaz Vahedi, Jean-Francois Chamberland, Aniruddha Datta, Edward R Dougherty
Primary Institution: Texas A&M University
Hypothesis
Can we develop a constrained intervention strategy to effectively manage gene regulatory networks while limiting the number of treatments?
Conclusion
The constrained intervention method can effectively reduce the likelihood of undesirable gene activity profiles while bounding the expected number of interventions.
Supporting Evidence
- The study demonstrates that constrained intervention can effectively alter the dynamics of a mutated mammalian cell cycle.
- Various control genes can be considered depending on the constraints imposed on the intervention policies.
- The results suggest that the most effective control gene may vary based on the restrictions on intervention.
Takeaway
This study looks at how to control gene activity in cancer cells while making sure not to give too many treatments, which can be harmful.
Methodology
The study formulates a constrained intervention strategy using probabilistic Boolean networks to model gene regulatory dynamics.
Limitations
The effectiveness of the intervention may vary based on the specific genes targeted and the constraints applied.
Digital Object Identifier (DOI)
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