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Inferring the relation between transcriptional and posttranscriptional regulation from expression compendia

Overview of attention for article published in BMC Microbiology, January 2014
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1 tweeter

Citations

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Title
Inferring the relation between transcriptional and posttranscriptional regulation from expression compendia
Published in
BMC Microbiology, January 2014
DOI 10.1186/1471-2180-14-14
Pubmed ID
Authors

Ivan Ishchukov, Yan Wu, Sandra Van Puyvelde, Jos Vanderleyden, Kathleen Marchal

Abstract

Publicly available expression compendia that measure both mRNAs and sRNAs provide a promising resource to simultaneously infer the transcriptional and the posttranscriptional network. To maximally exploit the information contained in such compendia, we propose an analysis flow that combines publicly available expression compendia and sequence-based predictions to infer novel sRNA-target interactions and to reconstruct the relation between the sRNA and the transcriptional network.

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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 29%
Student > Master 5 13%
Student > Ph. D. Student 4 11%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Other 5 13%
Unknown 9 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 39%
Biochemistry, Genetics and Molecular Biology 5 13%
Computer Science 4 11%
Immunology and Microbiology 1 3%
Psychology 1 3%
Other 2 5%
Unknown 10 26%

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 28 January 2014.
All research outputs
#18,361,534
of 22,741,406 outputs
Outputs from BMC Microbiology
#2,233
of 3,179 outputs
Outputs of similar age
#229,858
of 307,315 outputs
Outputs of similar age from BMC Microbiology
#59
of 77 outputs
Altmetric has tracked 22,741,406 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,179 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 15th percentile – i.e., 15% 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 307,315 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 77 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.