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Mendeley readers
Attention Score in Context
Chapter title |
Quantifying Entire Transcriptomes by Aligned RNA-Seq Data
|
---|---|
Chapter number | 10 |
Book title |
RNA Bioinformatics
|
Published in |
Methods in molecular biology, December 2014
|
DOI | 10.1007/978-1-4939-2291-8_10 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2290-1, 978-1-4939-2291-8
|
Authors |
Raffaele A Calogero, Francesca Zolezzi, Raffaele A. Calogero |
Editors |
Ernesto Picardi |
Abstract |
Massive Parallel Sequencing methods (MPS) can extend and improve the knowledge obtained by conventional microarray technology, both for mRNAs and noncoding RNAs. Although RNA quality and library preparation protocols are the main source of variability, the bioinformatics pipelines for RNA-seq data analysis are very complex and the choice of different tools at each stage of the analysis can significantly affect the overall results. In this chapter we describe the pipelines we use to detect miRNA and mRNA differential expression. |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 6% |
Unknown | 17 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 28% |
Researcher | 3 | 17% |
Student > Bachelor | 2 | 11% |
Student > Master | 1 | 6% |
Student > Doctoral Student | 1 | 6% |
Other | 2 | 11% |
Unknown | 4 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 6 | 33% |
Computer Science | 3 | 17% |
Agricultural and Biological Sciences | 2 | 11% |
Medicine and Dentistry | 2 | 11% |
Earth and Planetary Sciences | 1 | 6% |
Other | 1 | 6% |
Unknown | 3 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 16 January 2015.
All research outputs
#3,976,464
of 22,778,347 outputs
Outputs from Methods in molecular biology
#1,030
of 13,092 outputs
Outputs of similar age
#56,342
of 354,395 outputs
Outputs of similar age from Methods in molecular biology
#62
of 969 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,092 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 92% 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 354,395 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 84% of its contemporaries.
We're also able to compare this research output to 969 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.