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Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20

Overview of attention for article published in BMC Genomic Data, September 2018
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1 X user

Citations

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2 Dimensions

Readers on

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15 Mendeley
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Title
Data mining and machine learning approaches for the integration of genome-wide association and methylation data: methodology and main conclusions from GAW20
Published in
BMC Genomic Data, September 2018
DOI 10.1186/s12863-018-0646-3
Pubmed ID
Authors

Burcu Darst, Corinne D. Engelman, Ye Tian, Justo Lorenzo Bermejo

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 20%
Student > Bachelor 2 13%
Unspecified 1 7%
Student > Doctoral Student 1 7%
Student > Master 1 7%
Other 2 13%
Unknown 5 33%
Readers by discipline Count As %
Computer Science 3 20%
Medicine and Dentistry 2 13%
Business, Management and Accounting 1 7%
Unspecified 1 7%
Agricultural and Biological Sciences 1 7%
Other 1 7%
Unknown 6 40%
Attention Score in Context

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 September 2018.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from BMC Genomic Data
#861
of 1,204 outputs
Outputs of similar age
#273,047
of 350,978 outputs
Outputs of similar age from BMC Genomic Data
#18
of 28 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 16th percentile – i.e., 16% 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 350,978 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 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.