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Genomics, microRNA, epigenetics, and proteomics for future diagnosis, treatment and monitoring response in upper GI cancers

Overview of attention for article published in Clinical and Translational Medicine, April 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)

Mentioned by

twitter
7 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
61 Mendeley
Title
Genomics, microRNA, epigenetics, and proteomics for future diagnosis, treatment and monitoring response in upper GI cancers
Published in
Clinical and Translational Medicine, April 2016
DOI 10.1186/s40169-016-0093-6
Pubmed ID
Authors

Björn L. D. M. Brücher, Yan Li, Philipp Schnabel, Martin Daumer, Timothy J. Wallace, Rainer Kube, Bruno Zilberstein, Scott Steele, Jan L. A. Voskuil, Ijaz S. Jamall

Abstract

One major objective for our evolving understanding in the treatment of cancers will be to address how a combination of diagnosis and treatment strategies can be used to integrate patient and tumor variables with an outcome-oriented approach. Such an approach, in a multimodal therapy setting, could identify those patients (1) who should undergo a defined treatment (personalized therapy) (2) in whom modifications of the multimodal therapy due to observed responses might lead to an improvement of the response and/or prognosis (individualized therapy), (3) who might not benefit from a particular toxic treatment regimen, and (4) who could be identified early on and thereby be spared the morbidity associated with such treatments. These strategies could lead in the direction of precision medicine and there is hope of integrating translational molecular data to improve cancer classifications. In order to achieve these goals, it is necessary to understand the key issues in different aspects of biotechnology to anticipate future directions of personalized and individualized diagnosis and multimodal treatment strategies. Providing an overview of translational data in cancers proved to be a challenge as different methods and techniques used to obtain molecular data are used and studies are based on different tumor entities with different tumor biology and prognoses as well as vastly different therapeutic approaches. The pros and cons of the available methodologies and the potential response data in genomics, microRNA, epigenetics and proteomics with a focus on upper gastrointestinal cancers are considered herein to allow for an understanding of where these technologies stand with respect to cancer diagnosis, prognosis and treatment.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Belgium 1 2%
Unknown 59 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 18%
Student > Ph. D. Student 10 16%
Student > Bachelor 7 11%
Student > Master 6 10%
Other 5 8%
Other 10 16%
Unknown 12 20%
Readers by discipline Count As %
Medicine and Dentistry 23 38%
Biochemistry, Genetics and Molecular Biology 8 13%
Agricultural and Biological Sciences 7 11%
Computer Science 3 5%
Psychology 2 3%
Other 6 10%
Unknown 12 20%

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 03 September 2017.
All research outputs
#3,575,476
of 18,394,878 outputs
Outputs from Clinical and Translational Medicine
#75
of 414 outputs
Outputs of similar age
#63,976
of 272,552 outputs
Outputs of similar age from Clinical and Translational Medicine
#1
of 1 outputs
Altmetric has tracked 18,394,878 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 414 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done well, scoring higher than 81% 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 272,552 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 76% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them