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A robust linear regression based algorithm for automated evaluation of peptide identifications from shotgun proteomics by use of reversed-phase liquid chromatography retention time

Overview of attention for article published in BMC Bioinformatics, August 2008
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Mentioned by

patent
1 patent

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
32 Mendeley
citeulike
2 CiteULike
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Title
A robust linear regression based algorithm for automated evaluation of peptide identifications from shotgun proteomics by use of reversed-phase liquid chromatography retention time
Published in
BMC Bioinformatics, August 2008
DOI 10.1186/1471-2105-9-347
Pubmed ID
Authors

Hua Xu, Lanhao Yang, Michael A Freitas

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 28%
Researcher 8 25%
Student > Doctoral Student 2 6%
Professor > Associate Professor 2 6%
Student > Master 2 6%
Other 3 9%
Unknown 6 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 25%
Chemistry 4 13%
Biochemistry, Genetics and Molecular Biology 4 13%
Physics and Astronomy 3 9%
Computer Science 2 6%
Other 6 19%
Unknown 5 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 29 December 2022.
All research outputs
#7,705,696
of 23,437,201 outputs
Outputs from BMC Bioinformatics
#3,066
of 7,388 outputs
Outputs of similar age
#30,617
of 84,591 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 40 outputs
Altmetric has tracked 23,437,201 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 84,591 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.