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Evaluation of linear models and missing value imputation for the analysis of peptide-centric proteomics

Overview of attention for article published in BMC Bioinformatics, March 2019
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 X users

Citations

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20 Dimensions

Readers on

mendeley
54 Mendeley
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Title
Evaluation of linear models and missing value imputation for the analysis of peptide-centric proteomics
Published in
BMC Bioinformatics, March 2019
DOI 10.1186/s12859-019-2619-6
Pubmed ID
Authors

Philip Berg, Evan W. McConnell, Leslie M. Hicks, Sorina C. Popescu, George V. Popescu

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 26%
Researcher 11 20%
Student > Doctoral Student 5 9%
Student > Master 4 7%
Student > Bachelor 2 4%
Other 7 13%
Unknown 11 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 31%
Agricultural and Biological Sciences 6 11%
Medicine and Dentistry 5 9%
Computer Science 3 6%
Mathematics 2 4%
Other 9 17%
Unknown 12 22%
Attention Score in Context

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 17 March 2019.
All research outputs
#15,037,008
of 23,133,982 outputs
Outputs from BMC Bioinformatics
#5,091
of 7,337 outputs
Outputs of similar age
#208,914
of 351,896 outputs
Outputs of similar age from BMC Bioinformatics
#102
of 168 outputs
Altmetric has tracked 23,133,982 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 7,337 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% 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 351,896 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 168 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.