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LimiTT: link miRNAs to targets

Overview of attention for article published in BMC Bioinformatics, May 2016
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Title
LimiTT: link miRNAs to targets
Published in
BMC Bioinformatics, May 2016
DOI 10.1186/s12859-016-1070-1
Pubmed ID
Authors

Julia Bayer, Carsten Kuenne, Jens Preussner, Mario Looso

Abstract

MicroRNAs (miRNAs) impact various biological processes within animals and plants. They complementarily bind target mRNAs, effecting a post-transcriptional negative regulation on mRNA level. The investigation of miRNA target interactions (MTIs) by high throughput screenings is challenging, as frequently used in silico target prediction tools are prone to emit false positives. This issue is aggravated for niche model organisms, where validated miRNAs and MTIs both have to be transferred from well described model organisms. Even though DBs exist that contain experimentally validated MTIs, they are limited in their search options and they utilize different miRNA and target identifiers. The implemented pipeline LimiTT integrates four existing DBs containing experimentally validated MTIs. In contrast to other cumulative databases (DBs), LimiTT includes MTI data of 26 species. Additionally, the pipeline enables the identification and enrichment analysis of MTIs with and without species specificity based on dynamic quality criteria. Multiple tabular and graphical outputs are generated to permit the detailed assessment of results. Our freely available web-based pipeline LimiTT ( https://bioinformatics.mpi-bn.mpg.de/ ) is optimized to determine MTIs with and without species specification. It links miRNAs and/or putative targets with high granularity. The integrated mapping to homologous target identifiers enables the identification of MTIs not only for standard models, but for niche model organisms as well.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 6%
Unknown 31 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 27%
Student > Bachelor 6 18%
Student > Ph. D. Student 6 18%
Student > Master 4 12%
Professor > Associate Professor 3 9%
Other 4 12%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 36%
Computer Science 6 18%
Medicine and Dentistry 4 12%
Nursing and Health Professions 3 9%
Biochemistry, Genetics and Molecular Biology 3 9%
Other 5 15%
Attention Score in Context

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 18 May 2016.
All research outputs
#15,372,369
of 22,869,263 outputs
Outputs from BMC Bioinformatics
#5,385
of 7,296 outputs
Outputs of similar age
#187,838
of 309,572 outputs
Outputs of similar age from BMC Bioinformatics
#74
of 103 outputs
Altmetric has tracked 22,869,263 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,296 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 309,572 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.