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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Monitoring Dynamic Changes of the Cell Surface Glycoproteome by Quantitative Proteomics
|
|---|---|
| Chapter number | 3 |
| Book title |
Proteomics for Drug Discovery
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-7201-2_3 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7200-5, 978-1-4939-7201-2
|
| Authors |
Mathias Kalxdorf, Hans Christian Eberl, Marcus Bantscheff |
| Abstract |
The analysis of the cell surface accessible proteome provides invaluable information about cellular identity, cellular functions, and interactions. Cell surface labeling in combination with quantitative proteomics enables the unbiased identification and quantification of cell surface proteins. We describe a fast, efficient, and robust protocol for the enrichment of the N-linked plasma membrane glycoproteome and subsequent analysis by mass spectrometry. Precise and multiplexed quantification of relative changes of cell surface protein presentation is enabled by an isobaric labeling strategy. |
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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 33% |
| Other | 2 | 17% |
| Professor | 1 | 8% |
| Student > Bachelor | 1 | 8% |
| Professor > Associate Professor | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 2 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 25% |
| Agricultural and Biological Sciences | 2 | 17% |
| Computer Science | 2 | 17% |
| Chemistry | 2 | 17% |
| Medicine and Dentistry | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 2 | 17% |
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 19 August 2017.
All research outputs
#20,442,790
of 22,997,544 outputs
Outputs from Methods in molecular biology
#9,933
of 13,151 outputs
Outputs of similar age
#356,128
of 421,208 outputs
Outputs of similar age from Methods in molecular biology
#842
of 1,074 outputs
Altmetric has tracked 22,997,544 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 13,151 research outputs from this source. They receive a mean Attention Score of 3.4. 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 421,208 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 1,074 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.