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Intervention in biological phenomena modeled by S-systems
Nader Meskin1, Hazem N Nounou, Mohamed Nounou
1Department of Electrical Engineering, Qatar University, Doha 2713, Qatar. nader.meskin@qu.edu.qa
This study introduces direct and indirect intervention strategies for S-system models of biological phenomena. These methods effectively guide biological systems, like the glycolytic-glycogenolytic pathway, to desired states using advanced control algorithms.
Area of Science:
- Systems Biology
- Computational Biology
- Biochemical Pathway Modeling
Background:
- Biological phenomena modeling requires accurate yet flexible frameworks.
- S-systems offer a balance of accuracy and mathematical adaptability for dynamical biological modeling.
- Developing effective intervention strategies is crucial for controlling biological processes.
Purpose of the Study:
- To propose and evaluate novel direct and indirect intervention strategies for S-system models.
- To develop control algorithms for implementing these intervention strategies.
- To demonstrate the effectiveness of the proposed strategies on a relevant biological pathway.
Main Methods:
- Development of indirect intervention strategy using simple sampled-data control and model predictive control (MPC).
- Development of a direct intervention strategy employing MPC for target variable control.
- Application and simulation of both strategies on the glycolytic-glycogenolytic pathway.
Main Results:
- The indirect approach computes reference values for control inputs based on desired target variables.
- The direct approach utilizes MPC to directly steer target variables to their desired values.
- Simulation results confirm the efficacy of both proposed intervention strategies.
Conclusions:
- The proposed direct and indirect intervention strategies are effective for controlling biological systems modeled by S-systems.
- Model predictive control is a viable algorithm for implementing these intervention strategies.
- The glycolytic-glycogenolytic pathway serves as a successful test case for the developed methods.
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