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Models in Translational Oncology: A Public Resource Database for Preclinical Cancer Research

Overview of attention for article published in Cancer Research, May 2017
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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 (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

news
1 news outlet
twitter
5 tweeters

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
70 Mendeley
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Title
Models in Translational Oncology: A Public Resource Database for Preclinical Cancer Research
Published in
Cancer Research, May 2017
DOI 10.1158/0008-5472.can-16-3099
Pubmed ID
Authors

Claudia Galuschka, Rumyana Proynova, Benjamin Roth, Hellmut G. Augustin, Karin Müller-Decker

Abstract

The devastating diseases of human cancer are mimicked in basic and translational cancer research by a steadily increasing number of tumor models, a situation requiring a platform with standardized reports to share model data. Models in Translational Oncology (MiTO) database was developed as a unique Web platform aiming for a comprehensive overview of preclinical models covering genetically engineered organisms, models of transplantation, chemical/physical induction, or spontaneous development, reviewed here. MiTO serves data entry for metastasis profiles and interventions. Moreover, cell lines and animal lines including tool strains can be recorded. Hyperlinks for connection with other databases and file uploads as supplementary information are supported. Several communication tools are offered to facilitate exchange of information. Notably, intellectual property can be protected prior to publication by inventor-defined accessibility of any given model. Data recall is via a highly configurable keyword search. Genome editing is expected to result in changes of the spectrum of model organisms, a reason to open MiTO for species-independent data. Registered users may deposit own model fact sheets (FS). MiTO experts check them for plausibility. Independently, manually curated FS are provided to principle investigators for revision and publication. Importantly, noneditable versions of reviewed FS can be cited in peer-reviewed journals. Cancer Res; 77(10); 2557-63. ©2017 AACR.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
South Africa 1 1%
Unknown 68 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 23%
Student > Ph. D. Student 10 14%
Student > Master 9 13%
Student > Bachelor 8 11%
Other 4 6%
Other 7 10%
Unknown 16 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 19%
Pharmacology, Toxicology and Pharmaceutical Science 9 13%
Medicine and Dentistry 9 13%
Agricultural and Biological Sciences 8 11%
Chemistry 4 6%
Other 12 17%
Unknown 15 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 26 May 2022.
All research outputs
#2,188,774
of 21,419,046 outputs
Outputs from Cancer Research
#1,674
of 17,394 outputs
Outputs of similar age
#42,967
of 283,993 outputs
Outputs of similar age from Cancer Research
#36
of 174 outputs
Altmetric has tracked 21,419,046 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,394 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.4. This one has done particularly well, scoring higher than 90% 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 283,993 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 84% of its contemporaries.
We're also able to compare this research output to 174 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.