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New concepts for building vocabulary for cell image ontologies

Overview of attention for article published in BMC Bioinformatics, December 2011
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1 tweeter

Citations

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Readers on

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27 Mendeley
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2 CiteULike
Title
New concepts for building vocabulary for cell image ontologies
Published in
BMC Bioinformatics, December 2011
DOI 10.1186/1471-2105-12-487
Pubmed ID
Authors

Anne L Plant, John T Elliott, Talapady N Bhat

Abstract

There are significant challenges associated with the building of ontologies for cell biology experiments including the large numbers of terms and their synonyms. These challenges make it difficult to simultaneously query data from multiple experiments or ontologies. If vocabulary terms were consistently used and reused across and within ontologies, queries would be possible through shared terms. One approach to achieving this is to strictly control the terms used in ontologies in the form of a pre-defined schema, but this approach limits the individual researcher's ability to create new terms when needed to describe new experiments.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 7%
Peru 1 4%
Germany 1 4%
Mexico 1 4%
Russia 1 4%
Netherlands 1 4%
Unknown 20 74%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 37%
Student > Ph. D. Student 6 22%
Student > Master 2 7%
Librarian 2 7%
Professor 2 7%
Other 5 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 26%
Computer Science 6 22%
Engineering 2 7%
Chemistry 2 7%
Linguistics 2 7%
Other 8 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 November 2012.
All research outputs
#9,018,025
of 11,275,700 outputs
Outputs from BMC Bioinformatics
#3,509
of 4,195 outputs
Outputs of similar age
#215,956
of 306,650 outputs
Outputs of similar age from BMC Bioinformatics
#98
of 119 outputs
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So far Altmetric has tracked 4,195 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.