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TCLP: an online cancer cell line catalogue integrating HLA type, predicted neo-epitopes, virus and gene expression

Overview of attention for article published in Genome Medicine, November 2015
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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 (80th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
11 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
127 Mendeley
citeulike
1 CiteULike
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Title
TCLP: an online cancer cell line catalogue integrating HLA type, predicted neo-epitopes, virus and gene expression
Published in
Genome Medicine, November 2015
DOI 10.1186/s13073-015-0240-5
Pubmed ID
Authors

Jelle Scholtalbers, Sebastian Boegel, Thomas Bukur, Marius Byl, Sebastian Goerges, Patrick Sorn, Martin Loewer, Ugur Sahin, John C. Castle

Abstract

Human cancer cell lines are an important resource for research and drug development. However, the available annotations of cell lines are sparse, incomplete, and distributed in multiple repositories. Re-analyzing publicly available raw RNA-Seq data, we determined the human leukocyte antigen (HLA) type and abundance, identified expressed viruses and calculated gene expression of 1,082 cancer cell lines. Using the determined HLA types, public databases of cell line mutations, and existing HLA binding prediction algorithms, we predicted antigenic mutations in each cell line. We integrated the results into a comprehensive knowledgebase. Using the Django web framework, we provide an interactive user interface with advanced search capabilities to find and explore cell lines and an application programming interface to extract cell line information. The portal is available at http://celllines.tron-mainz.de .

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters 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 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 126 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 31 24%
Student > Ph. D. Student 21 17%
Student > Master 11 9%
Student > Bachelor 11 9%
Student > Postgraduate 10 8%
Other 23 18%
Unknown 20 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 34 27%
Agricultural and Biological Sciences 22 17%
Medicine and Dentistry 14 11%
Immunology and Microbiology 12 9%
Computer Science 4 3%
Other 17 13%
Unknown 24 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 2018.
All research outputs
#3,770,955
of 19,844,828 outputs
Outputs from Genome Medicine
#739
of 1,295 outputs
Outputs of similar age
#77,646
of 391,417 outputs
Outputs of similar age from Genome Medicine
#66
of 107 outputs
Altmetric has tracked 19,844,828 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,295 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 391,417 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 80% of its contemporaries.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.