On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP Experiments
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 (pre)processing represents an important issue. The a...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
|
| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2015/859849 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849305194317217792 |
|---|---|
| author | Stefan Kindermann Štěpán Papáček |
| author_facet | Stefan Kindermann Štěpán Papáček |
| author_sort | Stefan Kindermann |
| collection | DOAJ |
| description | 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 (pre)processing 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. |
| format | Article |
| id | doaj-art-083e5f83237d47e28659a6261318caee |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-083e5f83237d47e28659a6261318caee2025-08-20T03:55:32ZengWileyAbstract and Applied Analysis1085-33751687-04092015-01-01201510.1155/2015/859849859849On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP ExperimentsStefan Kindermann0Štěpán Papáček1Industrial Mathematics Institute, Johannes Kepler University of Linz, Altenbergerstr 69, 4040 Linz, AustriaInstitute 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 RepublicFluorescence 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 (pre)processing 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.http://dx.doi.org/10.1155/2015/859849 |
| spellingShingle | Stefan Kindermann Štěpán Papáček On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP Experiments Abstract and Applied Analysis |
| title | On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP Experiments |
| title_full | On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP Experiments |
| title_fullStr | On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP Experiments |
| title_full_unstemmed | On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP Experiments |
| title_short | On Data Space Selection and Data Processing for Parameter Identification in a Reaction-Diffusion Model Based on FRAP Experiments |
| title_sort | on data space selection and data processing for parameter identification in a reaction diffusion model based on frap experiments |
| url | http://dx.doi.org/10.1155/2015/859849 |
| work_keys_str_mv | AT stefankindermann ondataspaceselectionanddataprocessingforparameteridentificationinareactiondiffusionmodelbasedonfrapexperiments AT stepanpapacek ondataspaceselectionanddataprocessingforparameteridentificationinareactiondiffusionmodelbasedonfrapexperiments |