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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
A Guide to MethylationToActivity: A Deep Learning Framework That Reveals Promoter Activity Landscapes from DNA Methylomes in Individual Tumors.
|
---|---|
Chapter number | 6 |
Book title |
Computational Epigenomics and Epitranscriptomics
|
Published in |
Methods in molecular biology, January 2023
|
DOI | 10.1007/978-1-0716-2962-8_6 |
Pubmed ID | |
Book ISBNs |
978-1-07-162961-1, 978-1-07-162962-8
|
Authors |
Dieseldorff Jones, Karissa, Putnam, Daniel, Williams, Justin, Chen, Xiang |
Abstract |
Genome-wide DNA methylomes have contributed greatly to tumor detection and subclassification. However, interpreting the biological impact of the DNA methylome at the individual gene level remains a challenge. MethylationToActivity (M2A) is a pipeline that uses convolutional neural networks to infer H3K4me3 and H3K27ac enrichment from DNA methylomes and thus infer promoter activity. It was shown to be highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers. The following will present a user-friendly guide through the model pipeline. |
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 % |
---|---|---|
Unknown | 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 2 | 15% |
Researcher | 2 | 15% |
Student > Ph. D. Student | 1 | 8% |
Other | 1 | 8% |
Student > Doctoral Student | 1 | 8% |
Other | 1 | 8% |
Unknown | 5 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 3 | 23% |
Agricultural and Biological Sciences | 2 | 15% |
Chemistry | 1 | 8% |
Engineering | 1 | 8% |
Unknown | 6 | 46% |
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 01 February 2023.
All research outputs
#21,023,132
of 23,660,057 outputs
Outputs from Methods in molecular biology
#10,164
of 13,343 outputs
Outputs of similar age
#350,948
of 442,198 outputs
Outputs of similar age from Methods in molecular biology
#400
of 518 outputs
Altmetric has tracked 23,660,057 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,343 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% 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 442,198 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 518 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.