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Mendeley readers
Attention Score in Context
| Chapter title |
Experimental Design and Bioinformatic Analysis of DNA Methylation Data
|
|---|---|
| Chapter number | 10 |
| Book title |
CpG Islands
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7768-0_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7767-3, 978-1-4939-7768-0
|
| Authors |
Yulia Medvedeva, Alexander Shershebnev |
| Abstract |
DNA methylation is a crucial regulatory mechanism of gene expression, affected in many human pathologies. Therefore, it is not surprising that nowadays, in the era of high-throughput methods, a lot of data sets representing DNA methylation in various conditions are available and the amount of such data keeps growing. In this chapter, we discuss those aspects of experiment planning and data analysis, which we consider the most important for reliability and reproducibility of DNA methylation studies: usage of replicates, data quality control at various stages, selection of a statistical model, and incorporation of DNA methylation into the multi-omics analysis. |
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 % |
|---|---|---|
| United States | 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 36% |
| Student > Bachelor | 3 | 21% |
| Student > Doctoral Student | 2 | 14% |
| Professor | 1 | 7% |
| Unknown | 3 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 36% |
| Biochemistry, Genetics and Molecular Biology | 3 | 21% |
| Nursing and Health Professions | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Engineering | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 3 | 21% |
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 30 October 2019.
All research outputs
#18,594,219
of 23,031,582 outputs
Outputs from Methods in molecular biology
#7,974
of 13,177 outputs
Outputs of similar age
#330,599
of 442,391 outputs
Outputs of similar age from Methods in molecular biology
#950
of 1,499 outputs
Altmetric has tracked 23,031,582 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 13,177 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 442,391 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.