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Attention Score in Context
| Title |
Comparative analysis of microbiome measurement platforms using latent variable structural equation modeling
|
|---|---|
| Published in |
BMC Bioinformatics, March 2013
|
| DOI | 10.1186/1471-2105-14-79 |
| Pubmed ID | |
| Authors |
Xiao Wu, Kathryn Berkow, Daniel N Frank, Ellen Li, Ajay S Gulati, Wei Zhu |
| Abstract |
Culture-independent phylogenetic analysis of 16S ribosomal RNA (rRNA) gene sequences has emerged as an incisive method of profiling bacteria present in a specimen. Currently, multiple techniques are available to enumerate the abundance of bacterial taxa in specimens, including the Sanger sequencing, the 'next generation' pyrosequencing, microarrays, quantitative PCR, and the rapidly emerging, third generation sequencing, and fourth generation sequencing methods. An efficient statistical tool is in urgent need for the followings tasks: (1) to compare the agreement between these measurement platforms, (2) to select the most reliable platform(s), and (3) to combine different platforms of complementary strengths, for a unified analysis. |
X Demographics
The data shown below were collected from the profiles of 7 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 States | 4 | 57% |
| Germany | 1 | 14% |
| France | 1 | 14% |
| Unknown | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 71% |
| Members of the public | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 6% |
| United Kingdom | 1 | 1% |
| Japan | 1 | 1% |
| Pakistan | 1 | 1% |
| Unknown | 63 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 27% |
| Student > Ph. D. Student | 18 | 26% |
| Professor | 9 | 13% |
| Student > Master | 5 | 7% |
| Other | 4 | 6% |
| Other | 11 | 16% |
| Unknown | 4 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 37% |
| Medicine and Dentistry | 11 | 16% |
| Computer Science | 4 | 6% |
| Business, Management and Accounting | 4 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Other | 16 | 23% |
| Unknown | 6 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 04 May 2021.
All research outputs
#3,179,683
of 22,699,621 outputs
Outputs from BMC Bioinformatics
#1,175
of 7,254 outputs
Outputs of similar age
#27,449
of 194,736 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 143 outputs
Altmetric has tracked 22,699,621 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 83% 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 194,736 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 85% of its contemporaries.
We're also able to compare this research output to 143 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.