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Journal article

Optimized processing and analysis of conventional confocal microscopy generated scanning FCS data

Abstract:

Scanning Fluorescence Correlation Spectroscopy (scanning FCS) is a variant of conventional point FCS that allows molecular diffusion at multiple locations to be measured simultaneously. It enables disclosure of potential spatial heterogeneity in molecular diffusion dynamics and also the acquisition of a large amount of FCS data at the same time, providing large statistical accuracy. Here, we optimize the processing and analysis of these large-scale acquired sets of FCS data. On one hand we pr...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.ymeth.2017.09.010

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Oxford college:
Hertford College
Role:
Author
ORCID:
0000-0003-2685-4226
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
ORCID:
0000-0002-4457-8096
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
ORCID:
0000-0003-1196-6241
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
RDM
Sub department:
Weatherall Insti. of Molecular Medicine
Role:
Author
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Publisher:
Elsevier Publisher's website
Journal:
Methods Journal website
Volume:
140-141
Pages:
62-73
Publication date:
2017-09-28
Acceptance date:
2017-09-24
DOI:
EISSN:
1095-9130
ISSN:
1046-2023
Pmid:
28963070
Source identifiers:
732963
Language:
English
Keywords:
Pubs id:
pubs:732963
UUID:
uuid:5ed06b1f-775c-4db0-94b0-1f122e3f2a22
Local pid:
pubs:732963
Deposit date:
2019-07-08

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