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

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    SYSNO ASEP0444130
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeConference Paper
    TitleOn Two Methods for the Parameter Estimation Problem with Spatio-Temporal FRAP Data
    Author(s) Papáček, Š. (CZ)
    Jablonský, J. (CZ)
    Matonoha, Ctirad (UIVT-O) RID, SAI
    Source TitlePrograms 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. - ISBN 978-80-85823-64-6
    Pagess. 163-168
    Number of pages6 s.
    Publication formOnline - E
    ActionPrograms and Algorithms of Numerical Mathematics /17./
    Event date08.06.2014-13.06.2014
    VEvent locationDolní Maxov
    CountryCZ - Czech Republic
    Event typeCST
    Languageeng - English
    CountryCZ - Czech Republic
    Keywordsparameter estimation ; fluorescence recovery after photobleaching ; diffusion equation ; Moullineaux method ; Fisher information matrix ; sensitivity analysis ; confidence intervals ; uncertainty quantification
    Subject RIVBA - General Mathematics
    Institutional supportUIVT-O - RVO:67985807
    UT WOS000380564700023
    AnnotationFRAP (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.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2016
    Electronic addresshttp://dml.cz/handle/10338.dmlcz/702679
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