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High throughput sample processing and automated scoring

Overview of attention for article published in Frontiers in Genetics, October 2014
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Title
High throughput sample processing and automated scoring
Published in
Frontiers in Genetics, October 2014
DOI 10.3389/fgene.2014.00373
Pubmed ID
Authors

Gunnar Brunborg, Petra Jackson, Sergey Shaposhnikov, Hildegunn Dahl, Amaya Azqueta, Andrew R. Collins, Kristine B. Gutzkow

Abstract

The comet assay is a sensitive and versatile method for assessing DNA damage in cells. In the traditional version of the assay, there are many manual steps involved and few samples can be treated in one experiment. High throughput (HT) modifications have been developed during recent years, and they are reviewed and discussed. These modifications include accelerated scoring of comets; other important elements that have been studied and adapted to HT are cultivation and manipulation of cells or tissues before and after exposure, and freezing of treated samples until comet analysis and scoring. HT methods save time and money but they are useful also for other reasons: large-scale experiments may be performed which are otherwise not practicable (e.g., analysis of many organs from exposed animals, and human biomonitoring studies), and automation gives more uniform sample treatment and less dependence on operator performance. The HT modifications now available vary largely in their versatility, capacity, complexity, and costs. The bottleneck for further increase of throughput appears to be the scoring.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 20%
Student > Ph. D. Student 5 14%
Student > Bachelor 4 11%
Student > Master 4 11%
Professor 3 9%
Other 7 20%
Unknown 5 14%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 6 17%
Agricultural and Biological Sciences 5 14%
Biochemistry, Genetics and Molecular Biology 5 14%
Engineering 3 9%
Immunology and Microbiology 2 6%
Other 5 14%
Unknown 9 26%
Attention Score in Context

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 28 October 2014.
All research outputs
#14,787,304
of 22,766,595 outputs
Outputs from Frontiers in Genetics
#4,465
of 11,758 outputs
Outputs of similar age
#143,854
of 260,389 outputs
Outputs of similar age from Frontiers in Genetics
#74
of 113 outputs
Altmetric has tracked 22,766,595 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,758 research outputs from this source. They receive a mean Attention Score of 3.7. This one has gotten more attention than average, scoring higher than 54% 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 260,389 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.