Name
Title | ||
|---|---|---|
Nonuniform sampling for global optimization of kinetic rate constants in biological pathways |
Abstract | ||
|---|---|---|
Global optimization has proven to be a powerful tool for solving parameter estimation problems in biological applications, such as the estimation of kinetic rate constants in pathway models. These optimization algorithms sometimes suffer from slow convergence, stagnation or misconvergence to a non-optimal local minimum. Here we show that a nonuniform sampling method (implemented by running the optimization in a transformed space) can improve convergence and robustness for evolutionary-type algorithms, specifically Differential Evolution and Evolutionary Strategies. Results are shown from two case studies exemplifying the common problems of stagnation and misconvergence. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/WSC.2006.322934 | Winter Simulation Conference |
Keywords | Field | DocType |
parameter estimation problem,differential evolution,nonuniform sampling,optimization algorithm,slow convergence,evolutionary strategies,evolutionary-type algorithm,case study,biological pathway,common problem,global optimization,biological application,kinetic rate constant,evolutionary strategy,evolutionary computation,parameter estimation,biology,rate constant,kinetics,sampling methods,biological pathways | Convergence (routing),Mathematical optimization,Global optimization,Computer science,Evolutionary computation,Robustness (computer science),Differential evolution,Sampling (statistics),Estimation theory,Nonuniform sampling | Conference |
ISBN | Citations | PageRank |
1-4244-0501-7 | 3 | 0.42 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steven H Kleinstein | 1 | 95 | 16.45 |
| Dean Bottino | 2 | 3 | 0.42 |
| Anna Georgieva | 3 | 3 | 1.43 |
| Ramesh Sarangapani | 4 | 3 | 0.42 |
| G. Scott Lett | 5 | 3 | 0.42 |