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Modeling miRNA-mRNA interactions: fitting chemical kinetics equations to microarray data

Overview of attention for article published in BMC Systems Biology, February 2014
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  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
28 Mendeley
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Title
Modeling miRNA-mRNA interactions: fitting chemical kinetics equations to microarray data
Published in
BMC Systems Biology, February 2014
DOI 10.1186/1752-0509-8-19
Pubmed ID
Abstract

The miRNAs are small non-coding RNAs of roughly 22 nucleotides in length, which can bind with and inhibit protein coding mRNAs through complementary base pairing. By degrading mRNAs and repressing proteins, miRNAs regulate the cell signaling and cell functions. This paper focuses on innovative mathematical techniques to model gene interactions by algorithmic analysis of microarray data. Our goal was to elucidate which mRNAs were actually degraded or had their translation inhibited by miRNAs belonging to a very large pool of potential miRNAs.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Unknown 27 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 29%
Student > Ph. D. Student 7 25%
Student > Master 4 14%
Student > Doctoral Student 2 7%
Professor 2 7%
Other 4 14%
Unknown 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 36%
Biochemistry, Genetics and Molecular Biology 6 21%
Medicine and Dentistry 3 11%
Engineering 2 7%
Business, Management and Accounting 1 4%
Other 4 14%
Unknown 2 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 February 2014.
All research outputs
#5,214,813
of 9,738,606 outputs
Outputs from BMC Systems Biology
#495
of 954 outputs
Outputs of similar age
#86,604
of 182,608 outputs
Outputs of similar age from BMC Systems Biology
#20
of 48 outputs
Altmetric has tracked 9,738,606 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 954 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 43rd percentile – i.e., 43% 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 182,608 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.