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- W2544934433 abstract "Optimization is critical in the development and implementation of techniques for estimating the unmeasured dynamics of biological systems. Local-search algorithms present an attractive option for implementing this optimization due to their low complexity. These algorithms can, however, produce sub-optimal results when estimating these unmeasured dynamics using noisy measurements. In this work, we implement a global-search constrained optimization based on real-coded genetic algorithms (RC-GA) to estimate the unmeasured dynamics of the Caspases signal transduction network. We show that RC-GA performs better than gradient-based local search algorithms by providing estimates that more closely match the true dynamics of the biological system." @default.
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- W2544934433 date "2006-01-01" @default.
- W2544934433 modified "2023-09-26" @default.
- W2544934433 title "Estimating the Unmeasured Dynamics of Biological Systems using a Constrained Real-Coded Genetic Algorithm" @default.
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- W2544934433 doi "https://doi.org/10.1109/acssc.2006.355083" @default.
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