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Defining functional distances over Gene Ontology

Overview of attention for article published in BMC Bioinformatics, January 2008
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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1 Wikipedia page

Citations

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50 Dimensions

Readers on

mendeley
103 Mendeley
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14 CiteULike
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5 Connotea
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Title
Defining functional distances over Gene Ontology
Published in
BMC Bioinformatics, January 2008
DOI 10.1186/1471-2105-9-50
Pubmed ID
Authors

Angela del Pozo, Florencio Pazos, Alfonso Valencia

Abstract

A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. 'gene ontology' -GO-). However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform 'richness' of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
Brazil 3 3%
United Kingdom 3 3%
Spain 2 2%
France 2 2%
Germany 2 2%
Canada 1 <1%
Turkey 1 <1%
Russia 1 <1%
Other 3 3%
Unknown 81 79%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 33%
Researcher 28 27%
Student > Master 9 9%
Other 7 7%
Professor > Associate Professor 6 6%
Other 16 16%
Unknown 3 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 43%
Computer Science 35 34%
Biochemistry, Genetics and Molecular Biology 8 8%
Engineering 3 3%
Neuroscience 2 2%
Other 6 6%
Unknown 5 5%
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 30 December 2010.
All research outputs
#7,453,126
of 22,785,242 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,279 outputs
Outputs of similar age
#42,454
of 155,280 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 36 outputs
Altmetric has tracked 22,785,242 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 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 gotten more attention than average, scoring higher than 50% 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 155,280 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.