Benchmarking the S-tree based parameter estimation algorithm on biochemical networks

• Main Author: New, John Christopher T.
• Format: text
• Language: English
• Published: Animo Repository 2009
• Subjects: Benchmarking; Algorithms; Algorism; Simulation; Genetic programming (Computer science); Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/3748; https://animorepository.dlsu.edu.ph/context/etd_masteral/article/10586/viewcontent/CDTG004522_P.pdf
• Institution: De La Salle University

Biochemical networks contain valuable information that can be extracted for analysis. One important component is to determine the dynamics of a biochemical network and its structure. The representation of the biochemical network is modeled using the S-system model. This model needs its parameter to be estimated. A parameter estimation algorithm is used to estimate these parameters. There are different papers for parameter estimation algorithms available. Each one informs the result and capability of the algorithm. However, these are tested on different biochemical networks and the environmental configurations are most likely different. These may lead to difficulty in comparing to other algorithms. This study is part of a project that benchmarks other parameter estimation algorithm on uniform test data. The aim of this study is to focus on implementing and then benchmarking the S-tree based algorithm with the same uniform test data. The algorithm is tested on different biochemical networks. And, the performance of the algorithm is then analyzed. The performed analysis may provide a guide in exploring improvements for the algorithm and proceed to the implementation and benchmarking of the same test data as well. A test on inclusion of balancing of error and complexity is done to determine the improvement of the algorithm. In addition, the decoupling of the data is taken advantage and tested for effectiveness. Keywords: Benchmarking, Performance Analysis, Parameter Estimation, Biochemical Network, S-System, Simulation, S-tree, Genetic Programming, Balancing of Error and Complexity, Decoupling Biochemical networks contain valuable information that can be extracted for analysis. One important component is to determine the dynamics of a biochemical network and its structure. The representation of the biochemical network is modeled using the S-system model. This model needs its parameter to be estimated. A parameter estimation algorithm is used to estimate these parameters. There are different papers for parameter estimation algorithms available. Each one informs the result and capability of the algorithm. However, these are tested on different biochemical networks and the environmental configurations are most likely different. These may lead to difficulty in comparing to other algorithms. This study is part of a project that benchmarks other parameter estimation algorithm on uniform test data. The aim of this study is to focus on implementing and then benchmarking the S-tree based algorithm with the same uniform test data. The algorithm is tested on different biochemical networks. And, the performance of the algorithm is then analyzed. The performed analysis may provide a guide in exploring improvements for the algorithm and proceed to the implementation and benchmarking of the same test data as well. A test on inclusion of balancing of error and complexity is done to determine the improvement of the algorithm. In addition, the decoupling of the data is taken advantage and tested for effectiveness. Keywords: Benchmarking, Performance Analysis, Parameter Estimation, Biochemical Network, S-System, Simulation, S-tree, Genetic Programming, Balancing of Error and Complexity, Decoupling.