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Predicting the effects of frameshifting indels

Overview of attention for article published in Genome Biology, February 2012
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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 (93rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

blogs
1 blog
twitter
10 X users
wikipedia
4 Wikipedia pages

Citations

dimensions_citation
100 Dimensions

Readers on

mendeley
176 Mendeley
citeulike
3 CiteULike
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Title
Predicting the effects of frameshifting indels
Published in
Genome Biology, February 2012
DOI 10.1186/gb-2012-13-2-r9
Pubmed ID
Authors

Jing Hu, Pauline C Ng

Abstract

Each human has approximately 50 to 280 frameshifting indels, yet their implications are unknown. We created SIFT Indel, a prediction method for frameshifting indels that has 84% accuracy. The percentage of human frameshifting indels predicted to be gene-damaging is negatively correlated with allele frequency. We also show that although the first frameshifting indel in a gene causes loss of function, there is a tendency for the second frameshifting indel to compensate and restore protein function. SIFT Indel is available at http://sift-dna.org/www/SIFT_indels2.html.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 4%
Germany 2 1%
United Kingdom 2 1%
Brazil 1 <1%
Switzerland 1 <1%
Spain 1 <1%
Australia 1 <1%
Unknown 161 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 22%
Researcher 35 20%
Student > Master 29 16%
Student > Bachelor 16 9%
Professor > Associate Professor 9 5%
Other 29 16%
Unknown 19 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 36%
Biochemistry, Genetics and Molecular Biology 38 22%
Medicine and Dentistry 21 12%
Computer Science 10 6%
Immunology and Microbiology 4 2%
Other 13 7%
Unknown 27 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 11 January 2023.
All research outputs
#2,251,524
of 25,374,647 outputs
Outputs from Genome Biology
#1,859
of 4,467 outputs
Outputs of similar age
#16,652
of 254,241 outputs
Outputs of similar age from Genome Biology
#18
of 46 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 58% 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 254,241 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 46 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 60% of its contemporaries.