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Standardized benchmarking in the quest for orthologs

Overview of attention for article published in Nature Methods, April 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
56 X users
patent
1 patent
peer_reviews
1 peer review site

Citations

dimensions_citation
181 Dimensions

Readers on

mendeley
409 Mendeley
citeulike
5 CiteULike
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Title
Standardized benchmarking in the quest for orthologs
Published in
Nature Methods, April 2016
DOI 10.1038/nmeth.3830
Pubmed ID
Authors

Adrian M Altenhoff, Brigitte Boeckmann, Salvador Capella-Gutierrez, Daniel A Dalquen, Todd DeLuca, Kristoffer Forslund, Jaime Huerta-Cepas, Benjamin Linard, Cécile Pereira, Leszek P Pryszcz, Fabian Schreiber, Alan Sousa da Silva, Damian Szklarczyk, Clément-Marie Train, Peer Bork, Odile Lecompte, Christian von Mering, Ioannis Xenarios, Kimmen Sjölander, Lars Juhl Jensen, Maria J Martin, Matthieu Muffato, Toni Gabaldón, Suzanna E Lewis, Paul D Thomas, Erik Sonnhammer, Christophe Dessimoz

Abstract

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

X Demographics

X Demographics

The data shown below were collected from the profiles of 56 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 409 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
Spain 4 <1%
Germany 3 <1%
Switzerland 2 <1%
United Kingdom 2 <1%
France 1 <1%
Czechia 1 <1%
Canada 1 <1%
Finland 1 <1%
Other 4 <1%
Unknown 386 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 102 25%
Student > Ph. D. Student 98 24%
Student > Master 48 12%
Student > Bachelor 35 9%
Professor 19 5%
Other 60 15%
Unknown 47 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 174 43%
Biochemistry, Genetics and Molecular Biology 109 27%
Computer Science 28 7%
Immunology and Microbiology 8 2%
Environmental Science 6 1%
Other 21 5%
Unknown 63 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 54. 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 24 September 2023.
All research outputs
#738,259
of 24,494,826 outputs
Outputs from Nature Methods
#958
of 5,197 outputs
Outputs of similar age
#13,552
of 305,481 outputs
Outputs of similar age from Nature Methods
#15
of 95 outputs
Altmetric has tracked 24,494,826 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,197 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.8. This one has done well, scoring higher than 81% 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 305,481 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 95% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.