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Genome-wide detection of predicted non-coding RNAs in Rhizobium etli expressed during free-living and host-associated growth using a high-resolution tiling array

Overview of attention for article published in BMC Genomics, January 2010
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1 tweeter

Citations

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39 Dimensions

Readers on

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68 Mendeley
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1 CiteULike
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Title
Genome-wide detection of predicted non-coding RNAs in Rhizobium etli expressed during free-living and host-associated growth using a high-resolution tiling array
Published in
BMC Genomics, January 2010
DOI 10.1186/1471-2164-11-53
Pubmed ID
Authors

Maarten Vercruysse, Maarten Fauvart, Lore Cloots, Kristof Engelen, Inge M Thijs, Kathleen Marchal, Jan Michiels

Abstract

Non-coding RNAs (ncRNAs) play a crucial role in the intricate regulation of bacterial gene expression, allowing bacteria to quickly adapt to changing environments. In the past few years, a growing number of regulatory RNA elements have been predicted by computational methods, mostly in well-studied gamma-proteobacteria but lately in several alpha-proteobacteria as well. Here, we have compared an extensive compilation of these non-coding RNA predictions to intergenic expression data of a whole-genome high-resolution tiling array in the soil-dwelling alpha-proteobacterium Rhizobium etli.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 2 3%
Senegal 1 1%
France 1 1%
India 1 1%
Netherlands 1 1%
Spain 1 1%
Unknown 61 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 32%
Researcher 20 29%
Professor > Associate Professor 5 7%
Student > Master 5 7%
Student > Postgraduate 4 6%
Other 8 12%
Unknown 4 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 71%
Biochemistry, Genetics and Molecular Biology 6 9%
Environmental Science 4 6%
Medicine and Dentistry 3 4%
Immunology and Microbiology 1 1%
Other 2 3%
Unknown 4 6%

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 02 February 2013.
All research outputs
#10,995,790
of 12,373,620 outputs
Outputs from BMC Genomics
#6,415
of 7,296 outputs
Outputs of similar age
#218,729
of 259,888 outputs
Outputs of similar age from BMC Genomics
#513
of 625 outputs
Altmetric has tracked 12,373,620 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,296 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% 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 259,888 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 625 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.