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Controversies in modern evolutionary biology: the imperative for error detection and quality control

Overview of attention for article published in BMC Genomics, January 2012
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  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

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6 X users

Citations

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38 Dimensions

Readers on

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80 Mendeley
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1 CiteULike
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Title
Controversies in modern evolutionary biology: the imperative for error detection and quality control
Published in
BMC Genomics, January 2012
DOI 10.1186/1471-2164-13-5
Pubmed ID
Authors

Francisco Prosdocimi, Benjamin Linard, Pierre Pontarotti, Olivier Poch, Julie D Thompson

Abstract

The data from high throughput genomics technologies provide unique opportunities for studies of complex biological systems, but also pose many new challenges. The shift to the genome scale in evolutionary biology, for example, has led to many interesting, but often controversial studies. It has been suggested that part of the conflict may be due to errors in the initial sequences. Most gene sequences are predicted by bioinformatics programs and a number of quality issues have been raised, concerning DNA sequencing errors or badly predicted coding regions, particularly in eukaryotes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 6%
Brazil 2 3%
Canada 2 3%
Pakistan 1 1%
Sweden 1 1%
Germany 1 1%
United Kingdom 1 1%
Japan 1 1%
Spain 1 1%
Other 0 0%
Unknown 65 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 31%
Student > Ph. D. Student 16 20%
Professor > Associate Professor 7 9%
Student > Bachelor 6 8%
Professor 5 6%
Other 13 16%
Unknown 8 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 59%
Biochemistry, Genetics and Molecular Biology 9 11%
Computer Science 9 11%
Chemistry 2 3%
Chemical Engineering 1 1%
Other 3 4%
Unknown 9 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 18 November 2017.
All research outputs
#12,852,556
of 22,661,413 outputs
Outputs from BMC Genomics
#4,549
of 10,612 outputs
Outputs of similar age
#142,829
of 244,244 outputs
Outputs of similar age from BMC Genomics
#131
of 296 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,612 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 55% 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 244,244 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 296 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.