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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of miRNA-mRNA associations in Alzheimer’s disease mice using network topology
|
|---|---|
| Published in |
BMC Genomics, August 2014
|
| DOI | 10.1186/1471-2164-15-644 |
| Pubmed ID | |
| Authors |
Haneul Noh, Charny Park, Soojun Park, Young Seek Lee, Soo Young Cho, Hyemyung Seo |
| Abstract |
Little is known about the relationship between miRNA and mRNA expression in Alzheimer's disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms and anti-correlation profiles have been applied to predict miRNA targets using omics data, but this approach often leads to false positive predictions. Here, we applied the joint profiling analysis of mRNA and miRNA expression levels to Tg6799 AD model mice at 4 and 8 months of age using a network topology-based method. We constructed gene regulatory networks and used the PageRank algorithm to predict significant interactions between miRNA and mRNA. |
X Demographics
The data shown below were collected from the profiles of 12 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 | 4 | 33% |
| Spain | 1 | 8% |
| United States | 1 | 8% |
| Singapore | 1 | 8% |
| France | 1 | 8% |
| Unknown | 4 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 50% |
| Scientists | 4 | 33% |
| Science communicators (journalists, bloggers, editors) | 2 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Germany | 1 | 2% |
| Austria | 1 | 2% |
| Unknown | 56 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 22% |
| Student > Bachelor | 9 | 15% |
| Student > Master | 8 | 14% |
| Student > Ph. D. Student | 8 | 14% |
| Other | 5 | 8% |
| Other | 8 | 14% |
| Unknown | 8 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 27% |
| Biochemistry, Genetics and Molecular Biology | 10 | 17% |
| Computer Science | 5 | 8% |
| Neuroscience | 5 | 8% |
| Medicine and Dentistry | 4 | 7% |
| Other | 8 | 14% |
| Unknown | 11 | 19% |
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 15 October 2015.
All research outputs
#5,591,568
of 22,759,618 outputs
Outputs from BMC Genomics
#2,283
of 10,637 outputs
Outputs of similar age
#52,205
of 229,815 outputs
Outputs of similar age from BMC Genomics
#35
of 195 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 78% 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 229,815 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 77% of its contemporaries.
We're also able to compare this research output to 195 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.