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MetaPhOrs: orthology and paralogy predictions from multiple phylogenetic evidence using a consistency-based confidence score

Overview of attention for article published in Nucleic Acids Research, December 2010
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

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8 X users
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1 Q&A thread

Citations

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111 Dimensions

Readers on

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164 Mendeley
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9 CiteULike
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Title
MetaPhOrs: orthology and paralogy predictions from multiple phylogenetic evidence using a consistency-based confidence score
Published in
Nucleic Acids Research, December 2010
DOI 10.1093/nar/gkq953
Pubmed ID
Authors

Leszek P. Pryszcz, Jaime Huerta-Cepas, Toni Gabaldón

Abstract

Reliable prediction of orthology is central to comparative genomics. Approaches based on phylogenetic analyses closely resemble the original definition of orthology and paralogy and are known to be highly accurate. However, the large computational cost associated to these analyses is a limiting factor that often prevents its use at genomic scales. Recently, several projects have addressed the reconstruction of large collections of high-quality phylogenetic trees from which orthology and paralogy relationships can be inferred. This provides us with the opportunity to infer the evolutionary relationships of genes from multiple, independent, phylogenetic trees. Using such strategy, we combine phylogenetic information derived from different databases, to predict orthology and paralogy relationships for 4.1 million proteins in 829 fully sequenced genomes. We show that the number of independent sources from which a prediction is made, as well as the level of consistency across predictions, can be used as reliable confidence scores. A webserver has been developed to easily access these data (http://orthology.phylomedb.org), which provides users with a global repository of phylogeny-based orthology and paralogy predictions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 6 4%
United States 4 2%
Germany 3 2%
United Kingdom 3 2%
Brazil 2 1%
Sweden 1 <1%
Mexico 1 <1%
France 1 <1%
Romania 1 <1%
Other 3 2%
Unknown 139 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 27%
Researcher 42 26%
Student > Master 21 13%
Professor > Associate Professor 10 6%
Professor 10 6%
Other 28 17%
Unknown 9 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 101 62%
Biochemistry, Genetics and Molecular Biology 25 15%
Computer Science 15 9%
Medicine and Dentistry 3 2%
Environmental Science 2 1%
Other 5 3%
Unknown 13 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 January 2021.
All research outputs
#5,165,218
of 25,382,250 outputs
Outputs from Nucleic Acids Research
#7,771
of 27,719 outputs
Outputs of similar age
#32,313
of 193,013 outputs
Outputs of similar age from Nucleic Acids Research
#52
of 226 outputs
Altmetric has tracked 25,382,250 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 27,719 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has gotten more attention than average, scoring higher than 71% 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 193,013 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 83% of its contemporaries.
We're also able to compare this research output to 226 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.