On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP ExperimentsReport as inadecuate

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Abstract and Applied Analysis - Volume 2015 2015, Article ID 859849, 17 pages -

Research Article

Industrial Mathematics Institute, Johannes Kepler University of Linz, Altenbergerstr 69, 4040 Linz, Austria

Institute of Complex Systems, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Faculty of Fisheries and Protection of Waters, University of South Bohemia-České Budějovice, Zámek 136, 373 33 Nové Hrady, Czech Republic

Received 2 January 2015; Revised 15 May 2015; Accepted 18 May 2015

Academic Editor: Benito M. Chen-Charpentier

Copyright © 2015 Stefan Kindermann and Štěpán Papáček. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Fluorescence recovery after photobleaching FRAP is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data preprocessing represents an important issue. The aim of this paper is twofold. First, we formulate and solve the problem of relevant FRAP data selection. The theoretical findings are illustrated by the comparison of the results of parameter identification when the full data set was used and the case when the irrelevant data set data with negligible impact on the confidence interval of the estimated parameters was removed from the data space. Second, we analyze and compare two approaches of FRAP data processing. Our proposition, surprisingly for the FRAP community, claims that the data set represented by the FRAP recovery curves in form of a time series integrated data approach commonly used by the FRAP community leads to a larger confidence interval compared to the full spatiotemporal data approach.

Author: Stefan Kindermann and Štěpán Papáček

Source: https://www.hindawi.com/


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