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Parameters Identification for Mathematical Model of The Fission Yeast Cell Cycle Using Genetic Algorithm

Mostafavi Sabet, Azadeh | 2008

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 39277 (58)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Ghaffari, Ali
  7. Abstract:
  8. Soft computing consists of a set of powerful methods that have been successfully applied to many different application domains, including business, engineering, and bioinformatics. In this research we propose an innovative approach that uses genetic algorithms to mine a set of behavior data output by a biological system in order to determine the kinetic parameters of the system. In our approach, the machine learning method is integrated with the framework of existent biological information in a wiring diagram so that its findings are expressed in a form of system dynamic behavior. An application of the method to the cell division cycle model has shown that the method can discover optimum parametric values of the system and simulate the output behavior. It must be noted that a mathematical model of the cell cycle should be able to describe the physiology of a broad set of cell cycle mutants. Applying the proposed approach, we can discover optimum parametric values of mutant cell strains and simulate their behavior. Moreover using established principles of biochemical kinetics, we compare the properties of this model in detail with the observed behavior of mutant strains of fission yeast which have rapid division cycles of diminishing cell size and predict its behavior in consecutive cycles. By numerical simulations we show that the model is consistent with experiments for both wild type cells and mutant strains. In addition a comparison between the proposed modeling results and the previous work has been presented to evaluate the effectiveness of the approach and successfully shows that such application of genetic algorithms will highly improve the performance of mathematical model of cell division cycle to simulate such a complicated bio-system
  9. Keywords:
  10. Mathematical Modeling ; Genetic Algorithm ; Cell Cycle ; Fission Yeast ; Wiring Diagram

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