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Attention Score in Context
Chapter title |
Analyzing Prokaryotic RNA-Seq Data: A Case Study Identifying Holo-Fur Regulated Genes in Campylobacter jejuni.
|
---|---|
Chapter number | 20 |
Book title |
Campylobacter jejuni
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6536-6_20 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6534-2, 978-1-4939-6536-6
|
Authors |
Sophie Bérubé, James Butcher, Alain Stintzi |
Editors |
James Butcher, Alain Stintzi |
Abstract |
In recent years, RNA-seq has become an important method in the process of measuring gene expression in various cells and organisms. This chapter will detail all the bioinformatic steps that should be undertaken to determine differentially expressed genes from a typical RNA-seq experiment. Each step will be clearly explained in "non-bioinformatic" terminology so that readers embarking on RNA-seq analysis will be able to understand the rationale and reasoning behind each step. Moreover, the exact command lines used to process the data will be presented along with a description of the various flags and commands. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
China | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 6 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Professor | 1 | 17% |
Student > Bachelor | 1 | 17% |
Unknown | 4 | 67% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 1 | 17% |
Unknown | 5 | 83% |
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 27 November 2016.
All research outputs
#18,483,671
of 22,903,988 outputs
Outputs from Methods in molecular biology
#7,927
of 13,133 outputs
Outputs of similar age
#310,539
of 420,462 outputs
Outputs of similar age from Methods in molecular biology
#691
of 1,074 outputs
Altmetric has tracked 22,903,988 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 13,133 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% 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 420,462 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.