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Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network

Overview of attention for article published in BMC Medical Genomics, October 2012
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
16 Mendeley
citeulike
1 CiteULike
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Title
Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network
Published in
BMC Medical Genomics, October 2012
DOI 10.1186/1755-8794-5-43
Pubmed ID
Authors

Xin Chen, Wei Jiang, Qianghu Wang, Teng Huang, Peng Wang, Yan Li, Xiaowen Chen, Yingli Lv, Xia Li

Abstract

The identification of genes that predict in vitro cellular chemosensitivity of cancer cells is of great importance. Chemosensitivity related genes (CRGs) have been widely utilized to guide clinical and cancer chemotherapy decisions. In addition, CRGs potentially share functional characteristics and network features in protein interaction networks (PPIN).

Twitter Demographics

The data shown below were collected from the profiles of 2 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 25%
Student > Bachelor 3 19%
Professor > Associate Professor 2 13%
Student > Ph. D. Student 2 13%
Student > Master 1 6%
Other 1 6%
Unknown 3 19%
Readers by discipline Count As %
Computer Science 4 25%
Biochemistry, Genetics and Molecular Biology 2 13%
Agricultural and Biological Sciences 2 13%
Medicine and Dentistry 2 13%
Engineering 2 13%
Other 1 6%
Unknown 3 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 October 2012.
All research outputs
#1,981,833
of 4,508,612 outputs
Outputs from BMC Medical Genomics
#151
of 310 outputs
Outputs of similar age
#30,495
of 79,956 outputs
Outputs of similar age from BMC Medical Genomics
#6
of 14 outputs
Altmetric has tracked 4,508,612 research outputs across all sources so far. This one has received more attention than most of these and is in the 53rd percentile.
So far Altmetric has tracked 310 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 47th percentile – i.e., 47% 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 79,956 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 58% of its contemporaries.
We're also able to compare this research output to 14 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 50% of its contemporaries.