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Mendeley readers
Attention Score in Context
| Title |
Characterization and identification of protein O-GlcNAcylation sites with substrate specificity
|
|---|---|
| Published in |
BMC Bioinformatics, December 2014
|
| DOI | 10.1186/1471-2105-15-s16-s1 |
| Pubmed ID | |
| Authors |
Hsin-Yi Wu, Cheng-Tsung Lu, Hui-Ju Kao, Yi-Ju Chen, Yu-Ju Chen, Tzong-Yi Lee |
| Abstract |
Protein O-GlcNAcylation, involving the attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues. Elucidation of O-GlcNAcylation sites on proteins is required in order to decipher its crucial roles in regulating cellular processes and aid in drug design. With an increasing number of O-GlcNAcylation sites identified by mass spectrometry (MS)-based proteomics, several methods have been proposed for the computational identification of O-GlcNAcylation sites. However, no development that focuses on the investigation of O-GlcNAcylated substrate motifs has existed. Thus, we were motivated to design a new method for the identification of protein O-GlcNAcylation sites with the consideration of substrate site specificity. |
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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 33% |
| Student > Master | 4 | 17% |
| Student > Ph. D. Student | 4 | 17% |
| Student > Bachelor | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Other | 3 | 13% |
| Unknown | 1 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 29% |
| Agricultural and Biological Sciences | 6 | 25% |
| Computer Science | 3 | 13% |
| Medicine and Dentistry | 2 | 8% |
| Nursing and Health Professions | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 2 | 8% |
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 13 May 2015.
All research outputs
#20,247,117
of 22,775,504 outputs
Outputs from BMC Bioinformatics
#6,848
of 7,276 outputs
Outputs of similar age
#302,202
of 360,807 outputs
Outputs of similar age from BMC Bioinformatics
#135
of 138 outputs
Altmetric has tracked 22,775,504 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 7,276 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 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 360,807 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 138 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.