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A network-based approach to identify substrate classes of bacterial glycosyltransferases

Overview of attention for article published in BMC Genomics, May 2014
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Mentioned by

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3 tweeters

Citations

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202 Dimensions

Readers on

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69 Mendeley
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Title
A network-based approach to identify substrate classes of bacterial glycosyltransferases
Published in
BMC Genomics, May 2014
DOI 10.1186/1471-2164-15-349
Pubmed ID
Authors

Aminael Sánchez-Rodríguez, Hanne LP Tytgat, Joris Winderickx, Jos Vanderleyden, Sarah Lebeer, Kathleen Marchal

Abstract

Bacterial interactions with the environment- and/or host largely depend on the bacterial glycome. The specificities of a bacterial glycome are largely determined by glycosyltransferases (GTs), the enzymes involved in transferring sugar moieties from an activated donor to a specific substrate. Of these GTs their coding regions, but mainly also their substrate specificity are still largely unannotated as most sequence-based annotation flows suffer from the lack of characterized sequence motifs that can aid in the prediction of the substrate specificity.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ecuador 1 1%
Sweden 1 1%
South Africa 1 1%
Czechia 1 1%
Belgium 1 1%
Denmark 1 1%
Unknown 63 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 22%
Student > Master 10 14%
Student > Ph. D. Student 9 13%
Student > Bachelor 5 7%
Student > Postgraduate 5 7%
Other 13 19%
Unknown 12 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 43%
Biochemistry, Genetics and Molecular Biology 15 22%
Engineering 3 4%
Chemistry 2 3%
Social Sciences 2 3%
Other 4 6%
Unknown 13 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 January 2015.
All research outputs
#7,762,709
of 12,373,620 outputs
Outputs from BMC Genomics
#4,632
of 7,313 outputs
Outputs of similar age
#98,798
of 192,906 outputs
Outputs of similar age from BMC Genomics
#31
of 47 outputs
Altmetric has tracked 12,373,620 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,313 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 192,906 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.