# Planning identification experiments for cell signaling pathways: An NFκB case study

International Journal of Applied Mathematics and Computer Science (2010)

- Volume: 20, Issue: 4, page 773-780
- ISSN: 1641-876X

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topKrzysztof Fujarewicz. "Planning identification experiments for cell signaling pathways: An NFκB case study." International Journal of Applied Mathematics and Computer Science 20.4 (2010): 773-780. <http://eudml.org/doc/208025>.

@article{KrzysztofFujarewicz2010,

abstract = {Mathematical modeling of cell signaling pathways has become a very important and challenging problem in recent years. The importance comes from possible applications of obtained models. It may help us to understand phenomena appearing in single cells and cell populations on a molecular level. Furthermore, it may help us with the discovery of new drug therapies. Mathematical models of cell signaling pathways take different forms. The most popular way of mathematical modeling is to use a set of nonlinear ordinary differential equations (ODEs). It is very difficult to obtain a proper model. There are many hypotheses about the structure of the model (sets of variables and phenomena) that should be verified. The next step, fitting the parameters of the model, is also very complicated because of the nature of measurements. The blotting technique usually gives only semi-quantitative observations, which are very noisy and collected only at a limited number of time moments. The accuracy of parameter estimation may be significantly improved by a proper experiment design. Recently, we have proposed a gradient-based algorithm for the optimization of a sampling schedule. In this paper we use the algorithm in order to optimize a sampling schedule for the identification of the mathematical model of the NFκB regulatory module, known from the literature. We propose a two-stage optimization approach: a gradient-based procedure to find all stationary points and then pair-wise replacement for finding optimal numbers of replicates of measurements. Convergence properties of the presented algorithm are examined.},

author = {Krzysztof Fujarewicz},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {cell signaling pathways; experiment design; parameter estimation},

language = {eng},

number = {4},

pages = {773-780},

title = {Planning identification experiments for cell signaling pathways: An NFκB case study},

url = {http://eudml.org/doc/208025},

volume = {20},

year = {2010},

}

TY - JOUR

AU - Krzysztof Fujarewicz

TI - Planning identification experiments for cell signaling pathways: An NFκB case study

JO - International Journal of Applied Mathematics and Computer Science

PY - 2010

VL - 20

IS - 4

SP - 773

EP - 780

AB - Mathematical modeling of cell signaling pathways has become a very important and challenging problem in recent years. The importance comes from possible applications of obtained models. It may help us to understand phenomena appearing in single cells and cell populations on a molecular level. Furthermore, it may help us with the discovery of new drug therapies. Mathematical models of cell signaling pathways take different forms. The most popular way of mathematical modeling is to use a set of nonlinear ordinary differential equations (ODEs). It is very difficult to obtain a proper model. There are many hypotheses about the structure of the model (sets of variables and phenomena) that should be verified. The next step, fitting the parameters of the model, is also very complicated because of the nature of measurements. The blotting technique usually gives only semi-quantitative observations, which are very noisy and collected only at a limited number of time moments. The accuracy of parameter estimation may be significantly improved by a proper experiment design. Recently, we have proposed a gradient-based algorithm for the optimization of a sampling schedule. In this paper we use the algorithm in order to optimize a sampling schedule for the identification of the mathematical model of the NFκB regulatory module, known from the literature. We propose a two-stage optimization approach: a gradient-based procedure to find all stationary points and then pair-wise replacement for finding optimal numbers of replicates of measurements. Convergence properties of the presented algorithm are examined.

LA - eng

KW - cell signaling pathways; experiment design; parameter estimation

UR - http://eudml.org/doc/208025

ER -

## References

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