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Refining microRNA target predictions: Sorting the wheat from the chaff

Overview of attention for article published in Biochemical & Biophysical Research Communications, February 2014
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Article details
Title
Refining microRNA target predictions: Sorting the wheat from the chaff
Published in
Biochemical & Biophysical Research Communications, February 2014
DOI 10.1016/j.bbrc.2014.01.181
Pubmed ID
Authors
Abstract

microRNAs are short RNAs that reduce gene expression by binding to their targets. The accurate prediction of microRNA targets is essential to understanding the function of microRNAs. Computational predictions indicate that all human genes may be regulated by microRNAs, with each microRNA possibly targeting thousands of genes. Here we discuss computational methods for identifying mammalian microRNA targets and refining them for further experimental validation. We describe microRNA target prediction resources and procedures and how they integrate with various types of experimental techniques that aim to validate them or further explore their function. We also provide a list of target prediction databases and explain how these are curated.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 2%
United Kingdom 1 2%
Denmark 1 2%
Germany 1 2%
Unknown 60 94%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 16 25%
Student > Ph. D. Student 15 23%
Student > Doctoral Student 6 9%
Student > Master 6 9%
Student > Bachelor 5 8%
Other 10 16%
Unknown 6 9%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 28 44%
Biochemistry, Genetics and Molecular Biology 15 23%
Medicine and Dentistry 6 9%
Computer Science 4 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 2 3%
Unknown 7 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 February 2014.
All research outputs
#28,601,215
of 34,360,889 outputs
Outputs from Biochemical & Biophysical Research Communications
#28,508
of 33,075 outputs
Outputs of similar age
#306,435
of 379,806 outputs
Outputs of similar age from Biochemical & Biophysical Research Communications
#159
of 192 outputs
Altmetric has tracked 34,360,889 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 33,075 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 8th percentile – i.e., 8% 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 379,806 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 192 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.