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Split-alignment of genomes finds orthologies more accurately

Overview of attention for article published in Genome Biology, May 2015
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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 (86th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
11 X users
patent
1 patent
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

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91 Dimensions

Readers on

mendeley
92 Mendeley
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1 CiteULike
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Title
Split-alignment of genomes finds orthologies more accurately
Published in
Genome Biology, May 2015
DOI 10.1186/s13059-015-0670-9
Pubmed ID
Authors

Martin C Frith, Risa Kawaguchi

Abstract

We present a new pair-wise genome alignment method, based on a simple concept of finding an optimal set of local alignments. It gains accuracy by not masking repeats, and by using a statistical model to quantify the (un)ambiguity of each alignment part. Compared to previous animal genome alignments, it aligns thousands of locations differently and with much higher similarity, strongly suggesting that the previous alignments are non-orthologous. The previous methods suffer from an overly-strong assumption of long un-rearranged blocks. The new alignments should help find interesting and unusual features, such as fast-evolving elements and micro-rearrangements, which are confounded by alignment errors.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
France 1 1%
Netherlands 1 1%
Brazil 1 1%
Australia 1 1%
Unknown 84 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 28%
Student > Master 14 15%
Student > Bachelor 10 11%
Student > Ph. D. Student 9 10%
Professor > Associate Professor 8 9%
Other 10 11%
Unknown 15 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 39%
Biochemistry, Genetics and Molecular Biology 26 28%
Computer Science 11 12%
Environmental Science 3 3%
Unknown 16 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 04 February 2021.
All research outputs
#3,025,724
of 25,371,288 outputs
Outputs from Genome Biology
#2,270
of 4,467 outputs
Outputs of similar age
#37,262
of 280,389 outputs
Outputs of similar age from Genome Biology
#39
of 65 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% 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 is in the 48th percentile – i.e., 48% 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 280,389 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 86% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.