You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
RNA-Seq Experiment and Data Analysis.
|
---|---|
Chapter number | 9 |
Book title |
Estrogen Receptors
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3127-9_9 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3126-2, 978-1-4939-3127-9
|
Authors |
Liang, Hanquan, Zeng, Erliang, Hanquan Liang, Erliang Zeng |
Abstract |
With the ability to obtain tens of millions of reads, high-throughput messenger RNA sequencing (RNA-Seq) data offers the possibility of estimating abundance of isoforms and finding novel transcripts. In this chapter, we describe a protocol to construct an RNA-Seq library for sequencing on Illumina NGS platforms, and a computational pipeline to perform RNA-Seq data analysis. The protocols described in this chapter can be applied to the analysis of differential gene expression in control versus 17β-estradiol treatment of in vivo or in vitro systems. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Sweden | 1 | 4% |
Unknown | 26 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 26% |
Student > Ph. D. Student | 4 | 15% |
Professor > Associate Professor | 3 | 11% |
Student > Bachelor | 2 | 7% |
Professor | 1 | 4% |
Other | 1 | 4% |
Unknown | 9 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 15% |
Agricultural and Biological Sciences | 4 | 15% |
Medicine and Dentistry | 4 | 15% |
Computer Science | 3 | 11% |
Earth and Planetary Sciences | 1 | 4% |
Other | 0 | 0% |
Unknown | 11 | 41% |
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 24 November 2015.
All research outputs
#14,828,686
of 22,833,393 outputs
Outputs from Methods in molecular biology
#4,697
of 13,127 outputs
Outputs of similar age
#218,897
of 393,571 outputs
Outputs of similar age from Methods in molecular biology
#469
of 1,470 outputs
Altmetric has tracked 22,833,393 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,127 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 59% 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 393,571 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,470 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 63% of its contemporaries.