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Attention Score in Context
Chapter title |
Statistical Methods for Transcriptome-Wide Analysis of RNA Methylation by Bisulfite Sequencing
|
---|---|
Chapter number | 11 |
Book title |
RNA Methylation
|
Published in |
Methods in molecular biology, March 2017
|
DOI | 10.1007/978-1-4939-6807-7_11 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6805-3, 978-1-4939-6807-7
|
Authors |
Parker, Brian J., Brian J. Parker |
Editors |
Alexandra Lusser |
Abstract |
For the transcriptome-wide detection and quantification of the 5-methylcytosine (m(5)C) methylation modification of RNA, one experimental approach is via bisulfite conversion. In this chapter we discuss statistical methods, and a corresponding computational pipeline, to perform transcriptome-wide differential m(5)C methylation analysis between RNA samples, specialized for this assay. |
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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 9 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 2 | 22% |
Student > Bachelor | 2 | 22% |
Researcher | 2 | 22% |
Student > Master | 1 | 11% |
Other | 1 | 11% |
Other | 0 | 0% |
Unknown | 1 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 44% |
Nursing and Health Professions | 1 | 11% |
Agricultural and Biological Sciences | 1 | 11% |
Computer Science | 1 | 11% |
Chemistry | 1 | 11% |
Other | 0 | 0% |
Unknown | 1 | 11% |
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 31 March 2017.
All research outputs
#14,928,316
of 22,962,258 outputs
Outputs from Methods in molecular biology
#4,716
of 13,136 outputs
Outputs of similar age
#183,966
of 308,511 outputs
Outputs of similar age from Methods in molecular biology
#94
of 303 outputs
Altmetric has tracked 22,962,258 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 13,136 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 308,511 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 303 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 64% of its contemporaries.