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De novo protein sequence analysis of Macaca mulatta

Overview of attention for article published in BMC Genomics, August 2007
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1 Wikipedia page

Citations

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33 Mendeley
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Title
De novo protein sequence analysis of Macaca mulatta
Published in
BMC Genomics, August 2007
DOI 10.1186/1471-2164-8-270
Pubmed ID
Authors

Nilesh S Tannu, Scott E Hemby

Abstract

Macaca mulatta is one of the most utilized non-human primate species in biomedical research offering unique behavioral, neuroanatomical, and neurobiochemcial similarities to humans. This makes it a unique organism to model various diseases such as psychiatric and neurodegenerative illnesses while also providing insight into the complexities of the primate brain. A major obstacle in utilizing rhesus monkey models for human disease is the paucity of protein annotations for this species (~42,000 protein annotations) compared to 330,210 protein annotations for humans. The lack of available information limits the use of rhesus monkey for proteomic scale studies which rely heavily on database searches for protein identification. While characterization of proteins of interest from Macaca mulatta using the standard database search engines (e.g., MASCOT) can be accomplished, searches must be performed using a 'broad species database' which does not provide optimal confidence in protein annotation. Therefore, it becomes necessary to determine partial or complete amino acid sequences using either manual or automated de novo peptide sequence analysis methods.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Croatia 1 3%
Unknown 30 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 21%
Researcher 5 15%
Professor 4 12%
Student > Bachelor 3 9%
Student > Master 3 9%
Other 8 24%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 42%
Psychology 4 12%
Computer Science 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Chemistry 2 6%
Other 3 9%
Unknown 5 15%
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 08 November 2010.
All research outputs
#8,534,976
of 25,374,647 outputs
Outputs from BMC Genomics
#3,907
of 11,244 outputs
Outputs of similar age
#27,903
of 76,171 outputs
Outputs of similar age from BMC Genomics
#17
of 39 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 58% 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 76,171 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.