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A Digital Framework to Build, Visualize and Analyze a Gene Expression Atlas with Cellular Resolution in Zebrafish Early Embryogenesis

Overview of attention for article published in PLoS Computational Biology, June 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

twitter
6 tweeters
facebook
2 Facebook pages
reddit
1 Redditor

Readers on

mendeley
29 Mendeley
citeulike
2 CiteULike
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Title
A Digital Framework to Build, Visualize and Analyze a Gene Expression Atlas with Cellular Resolution in Zebrafish Early Embryogenesis
Published in
PLoS Computational Biology, June 2014
DOI 10.1371/journal.pcbi.1003670
Pubmed ID
Authors

Carlos Castro-González, Miguel A. Luengo-Oroz, Louise Duloquin, Thierry Savy, Barbara Rizzi, Sophie Desnoulez, René Doursat, Yannick L. Kergosien, María J. Ledesma-Carbayo, Paul Bourgine, Nadine Peyriéras, Andrés Santos

Abstract

A gene expression atlas is an essential resource to quantify and understand the multiscale processes of embryogenesis in time and space. The automated reconstruction of a prototypic 4D atlas for vertebrate early embryos, using multicolor fluorescence in situ hybridization with nuclear counterstain, requires dedicated computational strategies. To this goal, we designed an original methodological framework implemented in a software tool called Match-IT. With only minimal human supervision, our system is able to gather gene expression patterns observed in different analyzed embryos with phenotypic variability and map them onto a series of common 3D templates over time, creating a 4D atlas. This framework was used to construct an atlas composed of 6 gene expression templates from a cohort of zebrafish early embryos spanning 6 developmental stages from 4 to 6.3 hpf (hours post fertilization). They included 53 specimens, 181,415 detected cell nuclei and the segmentation of 98 gene expression patterns observed in 3D for 9 different genes. In addition, an interactive visualization software, Atlas-IT, was developed to inspect, supervise and analyze the atlas. Match-IT and Atlas-IT, including user manuals, representative datasets and video tutorials, are publicly and freely available online. We also propose computational methods and tools for the quantitative assessment of the gene expression templates at the cellular scale, with the identification, visualization and analysis of coexpression patterns, synexpression groups and their dynamics through developmental stages.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
United Kingdom 1 3%
Mexico 1 3%
United States 1 3%
Vietnam 1 3%
Netherlands 1 3%
Unknown 23 79%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 28%
Student > Ph. D. Student 7 24%
Professor 4 14%
Student > Master 4 14%
Student > Postgraduate 3 10%
Other 3 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 52%
Computer Science 5 17%
Biochemistry, Genetics and Molecular Biology 4 14%
Mathematics 2 7%
Physics and Astronomy 2 7%
Other 1 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 November 2014.
All research outputs
#1,224,257
of 6,649,277 outputs
Outputs from PLoS Computational Biology
#1,534
of 3,556 outputs
Outputs of similar age
#33,016
of 171,151 outputs
Outputs of similar age from PLoS Computational Biology
#51
of 148 outputs
Altmetric has tracked 6,649,277 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,556 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 171,151 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.