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Automatic workflow for the classification of local DNA conformations

Overview of attention for article published in BMC Bioinformatics, June 2013
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6 X users

Citations

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42 Mendeley
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Title
Automatic workflow for the classification of local DNA conformations
Published in
BMC Bioinformatics, June 2013
DOI 10.1186/1471-2105-14-205
Pubmed ID
Authors

Petr Čech, Jaromír Kukal, Jiří Černý, Bohdan Schneider, Daniel Svozil

Abstract

A growing number of crystal and NMR structures reveals a considerable structural polymorphism of DNA architecture going well beyond the usual image of a double helical molecule. DNA is highly variable with dinucleotide steps exhibiting a substantial flexibility in a sequence-dependent manner. An analysis of the conformational space of the DNA backbone and the enhancement of our understanding of the conformational dependencies in DNA are therefore important for full comprehension of DNA structural polymorphism.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Germany 1 2%
Unknown 40 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 26%
Researcher 9 21%
Student > Bachelor 5 12%
Student > Master 4 10%
Professor > Associate Professor 3 7%
Other 3 7%
Unknown 7 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 21%
Agricultural and Biological Sciences 7 17%
Computer Science 7 17%
Chemistry 7 17%
Engineering 2 5%
Other 2 5%
Unknown 8 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 25 June 2013.
All research outputs
#13,566,023
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#3,850
of 7,454 outputs
Outputs of similar age
#101,978
of 198,875 outputs
Outputs of similar age from BMC Bioinformatics
#43
of 84 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 45th percentile – i.e., 45% 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 198,875 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.