FRAP (Fluorescence Recovery After Photobleaching) is a measurement technique for determination of the mobility of fluorescent molecules (presumably due to the diffusion process) within the living cells. While the experimental setup and protocol are usually fixed, the method used for the model parameter estimation, i.e. the data processing step, is not well established. In order to enhance the quantitative analysis of experimental (noisy) FRAP data, we firstly formulate the inverse problem of model parameter estimation and then we focus on how the different methods of data pre- processing influence the confidence interval of the estimated parameters, namely the diffusion constant $p$. Finally, we present a preliminary study of two methods for the computation of a least-squares estimate $\widehat{p}$ and its confidence interval.

EUDML-ID : urn:eudml:doc:269903
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@article{702679,
     title = {On two methods for the parameter estimation problem with spatio-temporal FRAP data},
     booktitle = {Programs and Algorithms of Numerical Mathematics},
     series = {GDML\_Books},
     publisher = {Institute of Mathematics AS CR},
     address = {Prague},
     year = {2015},
     pages = {163-168},
     url = {http://dml.mathdoc.fr/item/702679}
}

Papáček, Štěpán; Jablonský, Jiří; Matonoha, Ctirad. On two methods for the parameter estimation problem with spatio-temporal FRAP data, dans Programs and Algorithms of Numerical Mathematics, GDML_Books,  (2015), pp. 163-168. http://gdmltest.u-ga.fr/item/702679/