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GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence

Overview of attention for article published in Frontiers in Genetics, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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Title
GLASSgo – Automated and Reliable Detection of sRNA Homologs From a Single Input Sequence
Published in
Frontiers in Genetics, April 2018
DOI 10.3389/fgene.2018.00124
Pubmed ID
Authors

Steffen C. Lott, Richard A. Schäfer, Martin Mann, Rolf Backofen, Wolfgang R. Hess, Björn Voß, Jens Georg

Abstract

Bacterial small RNAs (sRNAs) are important post-transcriptional regulators of gene expression. The functional and evolutionary characterization of sRNAs requires the identification of homologs, which is frequently challenging due to their heterogeneity, short length and partly, little sequence conservation. We developed the GLobal Automatic Small RNA Search go (GLASSgo) algorithm to identify sRNA homologs in complex genomic databases starting from a single sequence. GLASSgo combines an iterative BLAST strategy with pairwise identity filtering and a graph-based clustering method that utilizes RNA secondary structure information. We tested the specificity, sensitivity and runtime of GLASSgo, BLAST and the combination RNAlien/cmsearch in a typical use case scenario on 40 bacterial sRNA families. The sensitivity of the tested methods was similar, while the specificity of GLASSgo and RNAlien/cmsearch was significantly higher than that of BLAST. GLASSgo was on average ∼87 times faster than RNAlien/cmsearch, and only ∼7.5 times slower than BLAST, which shows that GLASSgo optimizes the trade-off between speed and accuracy in the task of finding sRNA homologs. GLASSgo is fully automated, whereas BLAST often recovers only parts of homologs and RNAlien/cmsearch requires extensive additional bioinformatic work to get a comprehensive set of homologs. GLASSgo is available as an easy-to-use web server to find homologous sRNAs in large databases.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 14%
Researcher 5 14%
Student > Bachelor 3 9%
Professor > Associate Professor 2 6%
Student > Ph. D. Student 2 6%
Other 3 9%
Unknown 15 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 29%
Agricultural and Biological Sciences 4 11%
Environmental Science 1 3%
Immunology and Microbiology 1 3%
Economics, Econometrics and Finance 1 3%
Other 3 9%
Unknown 15 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 21 April 2018.
All research outputs
#3,468,987
of 23,939,410 outputs
Outputs from Frontiers in Genetics
#1,092
of 12,864 outputs
Outputs of similar age
#69,664
of 330,478 outputs
Outputs of similar age from Frontiers in Genetics
#15
of 126 outputs
Altmetric has tracked 23,939,410 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,864 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 91% 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 330,478 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 78% of its contemporaries.
We're also able to compare this research output to 126 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.