On Two Methods for the Parameter Estimation Problem with Spatio-Temporal FRAP Data

0444130 - ÚI 2016 RIV CZ eng C - Konferenční příspěvek (zahraniční konf.)
Papáček, Š. - Jablonský, J. - Matonoha, Ctirad
On Two Methods for the Parameter Estimation Problem with Spatio-Temporal FRAP Data.
Programs and algorithms of numerical mathematics 17. Proceedings of seminar. Praha: Matematický ústav AV ČR, v.v.i, 2015 - (Chleboun, J.; Přikryl, P.; Segeth, K.; Šístek, J.; Vejchodský, T.), s. 163-168. ISBN 978-80-85823-64-6.
[Programs and Algorithms of Numerical Mathematics /17./. Dolní Maxov (CZ), 08.06.2014-13.06.2014]
Grant ostatní: GA MŠk(CZ) ED2.1.00/01.0024; GA MŠk(CZ) LO1205; GA MŠk(CZ) EE2.3.30.0006
Institucionální podpora: RVO:67985807
Klíčová slova: parameter estimation * fluorescence recovery after photobleaching * diffusion equation * Moullineaux method * Fisher information matrix * sensitivity analysis * confidence intervals * uncertainty quantification
Kód oboru RIV: BA - Obecná matematika
http://dml.cz/handle/10338.dmlcz/702679

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 $\hat{p}$ and its confidence interval.
Trvalý link: http://hdl.handle.net/11104/0246708