Evidence map›Paper›PMID 21928120›Full record

ArticleEuropean biophysics journal : EBJ2011

Automated multidimensional single molecule fluorescence microscopy feature detection and tracking.

Daniel J Rolfe, Charles I McLachlan, Michael Hirsch, Sarah R Needham, Christopher J Tynan, Stephen E D Webb, Marisa L Martin-Fernandez, Michael P Hobson

Abstract read
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In one paragraph

Article in European biophysics journal : EBJ, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

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  9. The cell wall regulates dynamics and size of plasma-membrane nanodomains inProceedings of the National Academy of Sciences of the United States of America · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Daniel J RolfeCentral Laser Facility, Science and Technology Facilities Council, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxon, UK.
Charles I McLachlan
Michael Hirsch
Sarah R Needham
Christopher J Tynan
Stephen E D Webb
Marisa L Martin-Fernandez
Michael P Hobson

Funding

Biotechnology and Biological Sciences Research Council BB/E000215/1Biotechnology and Biological Sciences Research Council BB/G006911/1Biotechnology and Biological Sciences Research Council BB/G007160/1
6 · The paper itself

Abstract

Characterisation of multi-protein interactions in cellular networks can be achieved by optical microscopy using multidimensional single molecule fluorescence imaging. Proteins of different species, individually labelled with a single fluorophore, can be imaged as isolated spots (features) of different colour light in different channels, and their diffusive behaviour in cells directly measured through time. Challenges in data analysis have, however, thus far hindered its application in biology. A set of methods for the automated analysis of multidimensional single molecule microscopy data from cells is presented, incorporating Bayesian segmentation-based feature detection, image registration and particle tracking. Single molecules of different colours can be simultaneously detected in noisy, high background data with an arbitrary number of channels, acquired simultaneously or time-multiplexed, and then tracked through time. The resulting traces can be further analysed, for example to detect intensity steps, count discrete intensity levels, measure fluorescence resonance energy transfer (FRET) or changes in polarisation. Examples are shown illustrating the use of the algorithms in investigations of the epidermal growth factor receptor (EGFR) signalling network, a key target for cancer therapeutics, and with simulated data.

Indexed as

AlgorithmsAutomationBayes TheoremCell Line, TumorErbB ReceptorsFluorescence Resonance Energy TransferHumansImage Processing, Computer-AssistedMicroscopy, FluorescenceErbB Receptors

Identifiers

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.