↓ Skip to main content

Prediction of miRNA-mRNA associations in Alzheimer’s disease mice using network topology

Overview of attention for article published in BMC Genomics, January 2014
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
12 tweeters

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
36 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Prediction of miRNA-mRNA associations in Alzheimer’s disease mice using network topology
Published in
BMC Genomics, January 2014
DOI 10.1186/1471-2164-15-644
Pubmed ID
Authors

Haneul Noh, Charny Park, Soojun Park, Young Lee, Soo 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.

Twitter Demographics

The data shown below were collected from the profiles of 12 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
United Kingdom 1 3%
Austria 1 3%
Unknown 33 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 28%
Student > Master 7 19%
Student > Ph. D. Student 7 19%
Other 4 11%
Student > Bachelor 3 8%
Other 5 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 42%
Biochemistry, Genetics and Molecular Biology 6 17%
Computer Science 4 11%
Unspecified 3 8%
Medicine and Dentistry 3 8%
Other 5 14%

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
#2,615,496
of 12,378,406 outputs
Outputs from BMC Genomics
#1,315
of 7,251 outputs
Outputs of similar age
#37,753
of 200,976 outputs
Outputs of similar age from BMC Genomics
#34
of 252 outputs
Altmetric has tracked 12,378,406 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,251 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 81% 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 200,976 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 81% of its contemporaries.
We're also able to compare this research output to 252 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.