↓ Skip to main content

An integrative approach to ortholog prediction for disease-focused and other functional studies

Overview of attention for article published in BMC Bioinformatics, August 2011
Altmetric Badge

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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
1 blog
twitter
6 X users

Citations

dimensions_citation
627 Dimensions

Readers on

mendeley
417 Mendeley
citeulike
3 CiteULike
connotea
1 Connotea
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
An integrative approach to ortholog prediction for disease-focused and other functional studies
Published in
BMC Bioinformatics, August 2011
DOI 10.1186/1471-2105-12-357
Pubmed ID
Authors

Yanhui Hu, Ian Flockhart, Arunachalam Vinayagam, Clemens Bergwitz, Bonnie Berger, Norbert Perrimon, Stephanie E Mohr

Abstract

Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward.

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 417 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
Germany 2 <1%
France 1 <1%
United Kingdom 1 <1%
Denmark 1 <1%
Canada 1 <1%
Japan 1 <1%
Romania 1 <1%
Unknown 405 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 104 25%
Researcher 75 18%
Student > Master 50 12%
Student > Bachelor 34 8%
Professor 20 5%
Other 58 14%
Unknown 76 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 124 30%
Agricultural and Biological Sciences 118 28%
Neuroscience 34 8%
Computer Science 15 4%
Medicine and Dentistry 15 4%
Other 33 8%
Unknown 78 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 April 2016.
All research outputs
#2,828,153
of 22,651,245 outputs
Outputs from BMC Bioinformatics
#978
of 7,236 outputs
Outputs of similar age
#14,856
of 124,934 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 79 outputs
Altmetric has tracked 22,651,245 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 7,236 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 86% 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 124,934 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 88% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.