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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 (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
13 tweeters
facebook
2 Facebook pages

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
140 Mendeley
citeulike
1 CiteULike
Summary Twitter Facebook Dimensions citations
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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
26589293
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 .

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Twitter Demographics

The data shown below were collected from the profiles of 13 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 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 139 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 24%
Student > Ph. D. Student 21 15%
Student > Bachelor 12 9%
Other 11 8%
Student > Master 11 8%
Other 25 18%
Unknown 27 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 24%
Agricultural and Biological Sciences 24 17%
Medicine and Dentistry 15 11%
Immunology and Microbiology 14 10%
Computer Science 5 4%
Other 18 13%
Unknown 31 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 21 July 2022.
All research outputs
#3,990,800
of 22,896,955 outputs
Outputs from Genome Medicine
#815
of 1,443 outputs
Outputs of similar age
#65,960
of 386,740 outputs
Outputs of similar age from Genome Medicine
#17
of 44 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,443 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one is in the 43rd percentile – i.e., 43% 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 386,740 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 82% of its contemporaries.
We're also able to compare this research output to 44 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 63% of its contemporaries.

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