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Comparison, alignment, and synchronization of cell line information between CLO and EFO

Overview of attention for article published in BMC Bioinformatics, December 2017
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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3 X users
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1 Wikipedia page

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17 Mendeley
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Title
Comparison, alignment, and synchronization of cell line information between CLO and EFO
Published in
BMC Bioinformatics, December 2017
DOI 10.1186/s12859-017-1979-z
Pubmed ID
Authors

Edison Ong, Sirarat Sarntivijai, Simon Jupp, Helen Parkinson, Yongqun He

Abstract

The Experimental Factor Ontology (EFO) is an application ontology driven by experimental variables including cell lines to organize and describe the diverse experimental variables and data resided in the EMBL-EBI resources. The Cell Line Ontology (CLO) is an OBO community-based ontology that contains information of immortalized cell lines and relevant experimental components. EFO integrates and extends ontologies from the bio-ontology community to drive a number of practical applications. It is desirable that the community shares design patterns and therefore that EFO reuses the cell line representation from the Cell Line Ontology (CLO). There are, however, challenges to be addressed when developing a common ontology design pattern for representing cell lines in both EFO and CLO. In this study, we developed a strategy to compare and map cell line terms between EFO and CLO. We examined Cellosaurus resources for EFO-CLO cross-references. Text labels of cell lines from both ontologies were verified by biological information axiomatized in each source. The study resulted in the identification 873 EFO-CLO aligned and 344 EFO unique immortalized permanent cell lines. All of these cell lines were updated to CLO and the cell line related information was merged. A design pattern that integrates EFO and CLO was also developed. Our study compared, aligned, and synchronized the cell line information between CLO and EFO. The final updated CLO will be examined as the candidate ontology to import and replace eligible EFO cell line classes thereby supporting the interoperability in the bio-ontology domain. Our mapping pipeline illustrates the use of ontology in aiding biological data standardization and integration through the biological and semantics content of cell lines.

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X Demographics

The data shown below were collected from the profiles of 3 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Other 3 18%
Researcher 3 18%
Student > Ph. D. Student 2 12%
Student > Bachelor 2 12%
Librarian 1 6%
Other 2 12%
Unknown 4 24%
Readers by discipline Count As %
Computer Science 6 35%
Agricultural and Biological Sciences 3 18%
Engineering 2 12%
Medicine and Dentistry 1 6%
Business, Management and Accounting 1 6%
Other 0 0%
Unknown 4 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 October 2021.
All research outputs
#6,109,292
of 23,012,811 outputs
Outputs from BMC Bioinformatics
#2,269
of 7,315 outputs
Outputs of similar age
#121,819
of 440,658 outputs
Outputs of similar age from BMC Bioinformatics
#40
of 138 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,315 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 68% 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 440,658 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.