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Attention Score in Context
Chapter title |
Single Cell Protein Analysis
|
---|---|
Chapter number | 5 |
Book title |
Single Cell Protein Analysis
|
Published in |
Methods in molecular biology, January 2015
|
DOI | 10.1007/978-1-4939-2987-0_5 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2986-3, 978-1-4939-2987-0
|
Authors |
Taniguchi, Yuichi, Yuichi Taniguchi |
Abstract |
Single-cell proteomic and transcriptomic analysis is an emerging approach for providing quantitative and comprehensive characterization of gene functions in individual cells. This analysis, however, is often hampered by insufficient sensitivity for detecting low copy gene expression products such as transcription factors and regulators. Here I describe a method for the quantitative genome-wide analysis of single-cell protein and mRNA copy numbers with single molecule sensitivity for the model organism Escherichia coli. |
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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 1 | 9% |
Unknown | 10 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 4 | 36% |
Unspecified | 1 | 9% |
Student > Bachelor | 1 | 9% |
Other | 1 | 9% |
Student > Ph. D. Student | 1 | 9% |
Other | 1 | 9% |
Unknown | 2 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 36% |
Engineering | 2 | 18% |
Agricultural and Biological Sciences | 2 | 18% |
Unspecified | 1 | 9% |
Unknown | 2 | 18% |
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 2016.
All research outputs
#18,467,727
of 22,883,326 outputs
Outputs from Methods in molecular biology
#7,923
of 13,131 outputs
Outputs of similar age
#256,121
of 353,371 outputs
Outputs of similar age from Methods in molecular biology
#481
of 997 outputs
Altmetric has tracked 22,883,326 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,131 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% 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 353,371 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 997 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.