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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Current applications of antibody microarrays
|
|---|---|
| Published in |
Clinical Proteomics, February 2018
|
| DOI | 10.1186/s12014-018-9184-2 |
| Pubmed ID | |
| Authors |
Ziqing Chen, Tea Dodig-Crnković, Jochen M. Schwenk, Sheng-ce Tao |
| Abstract |
The concept of antibody microarrays is one of the most versatile approaches within multiplexed immunoassay technologies. These types of arrays have increasingly become an attractive tool for the exploratory detection and study of protein abundance, function, pathways, and potential drug targets. Due to the properties of the antibody microarrays and their potential use in basic research and clinical analytics, various types of antibody microarrays have already been developed. In spite of the growing number of studies utilizing this technique, few reviews about antibody microarray technology have been presented to reflect the quality and future uses of the generated data. In this review, we provide a summary of the recent applications of antibody microarray techniques in basic biology and clinical studies, providing insights into the current trends and future of protein analysis. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 163 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 13% |
| Student > Bachelor | 22 | 13% |
| Researcher | 18 | 11% |
| Student > Master | 16 | 10% |
| Other | 10 | 6% |
| Other | 20 | 12% |
| Unknown | 55 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 38 | 23% |
| Agricultural and Biological Sciences | 13 | 8% |
| Engineering | 13 | 8% |
| Medicine and Dentistry | 9 | 6% |
| Immunology and Microbiology | 8 | 5% |
| Other | 19 | 12% |
| Unknown | 63 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 June 2023.
All research outputs
#4,269,184
of 24,129,125 outputs
Outputs from Clinical Proteomics
#47
of 298 outputs
Outputs of similar age
#80,083
of 334,131 outputs
Outputs of similar age from Clinical Proteomics
#5
of 8 outputs
Altmetric has tracked 24,129,125 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done well, scoring higher than 84% 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 334,131 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.