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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Cell-Specific Labeling for Analyzing Bidirectional Signaling by Mass Spectrometry
|
|---|---|
| Chapter number | 14 |
| Book title |
Kinase Signaling Networks
|
| Published in |
Methods in molecular biology, July 2017
|
| DOI | 10.1007/978-1-4939-7154-1_14 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7152-7, 978-1-4939-7154-1
|
| Authors |
Christopher J. Tape, Claus Jørgensen |
| Abstract |
Cell-specific proteome labeling enables global proteome-wide analysis of cell signaling in heterotypic co-cultures. Such approaches have provided unique insight in contact-initiated receptor tyrosine kinase signaling, transfer of proteomic material between heterotypic cells, and interactions between normal and oncogenic cells. Here we describe current methods for cell-specific labeling of heterotypic cells with isotopic labeled amino acids (e.g., SILAC and CTAP). We outline the advantages and disadvantages of individual approaches, describe typical experimental scenarios, and discuss where each experimental approach is optimally applied. |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 45% |
| United States | 2 | 18% |
| South Africa | 1 | 9% |
| Spain | 1 | 9% |
| Unknown | 2 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 73% |
| Science communicators (journalists, bloggers, editors) | 2 | 18% |
| Scientists | 1 | 9% |
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% |
| Researcher | 2 | 17% |
| Unspecified | 1 | 8% |
| Lecturer | 1 | 8% |
| Unknown | 4 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 42% |
| Unspecified | 1 | 8% |
| Chemistry | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Unknown | 4 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 July 2017.
All research outputs
#4,748,235
of 22,990,068 outputs
Outputs from Methods in molecular biology
#1,384
of 13,150 outputs
Outputs of similar age
#82,886
of 314,579 outputs
Outputs of similar age from Methods in molecular biology
#14
of 270 outputs
Altmetric has tracked 22,990,068 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,150 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 88% 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 314,579 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 270 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.