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Analysis options for high-throughput sequencing in miRNA expression profiling

Overview of attention for article published in BMC Research Notes, March 2014
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  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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2 X users
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1 Google+ user

Citations

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Readers on

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116 Mendeley
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1 CiteULike
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Title
Analysis options for high-throughput sequencing in miRNA expression profiling
Published in
BMC Research Notes, March 2014
DOI 10.1186/1756-0500-7-144
Pubmed ID
Authors

Tomasz Stokowy, Markus Eszlinger, Michał Świerniak, Krzysztof Fujarewicz, Barbara Jarząb, Ralf Paschke, Knut Krohn

Abstract

Recently high-throughput sequencing (HTS) using next generation sequencing techniques became useful in digital gene expression profiling.Our study introduces analysis options for HTS data based on mapping to miRBase or counting and grouping of identical sequence reads. Those approaches allow a hypothesis free detection of miRNA differential expression.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
Italy 1 <1%
South Africa 1 <1%
Brazil 1 <1%
Unknown 110 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 22%
Researcher 22 19%
Student > Master 13 11%
Student > Bachelor 12 10%
Student > Doctoral Student 7 6%
Other 18 16%
Unknown 18 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 41%
Biochemistry, Genetics and Molecular Biology 27 23%
Medicine and Dentistry 9 8%
Engineering 3 3%
Nursing and Health Professions 2 2%
Other 6 5%
Unknown 21 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 March 2014.
All research outputs
#13,405,680
of 22,749,166 outputs
Outputs from BMC Research Notes
#1,680
of 4,262 outputs
Outputs of similar age
#109,508
of 221,235 outputs
Outputs of similar age from BMC Research Notes
#34
of 81 outputs
Altmetric has tracked 22,749,166 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 58% 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 221,235 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 81 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.