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Exploring possible DNA structures in real-time polymerase kinetics using Pacific Biosciences sequencer data

Overview of attention for article published in BMC Bioinformatics, January 2015
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  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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Article details
Title
Exploring possible DNA structures in real-time polymerase kinetics using Pacific Biosciences sequencer data
Published in
BMC Bioinformatics, January 2015
DOI 10.1186/s12859-014-0449-0
Pubmed ID
Authors
Abstract

BackgroundPausing of DNA polymerase can indicate the presence of a DNA structure that differs from the canonical double-helix. Here we detail a method to investigate how polymerase pausing in the Pacific Biosciences sequencer reads can be related to DNA sequences. The Pacific Biosciences sequencer uses optics to view a polymerase and its interaction with a single DNA molecule in real-time, offering a unique way to detect potential alternative DNA structures.ResultsWe have developed a new way to examine polymerase kinetics data and relate it to the DNA sequence by using a wavelet transform of read information from the sequencer. We use this method to examine how polymerase kinetics are related to nucleotide base composition. We then examine tandem repeat sequences known for their ability to form different DNA structures: (CGG)n and (CG)n repeats which can, respectively, form G-quadruplex DNA and Z-DNA. We find pausing around the (CGG)n repeat that may indicate the presence of G-quadruplexes in some of the sequencer reads. The (CG)n repeat does not appear to cause polymerase pausing, but its kinetics signature nevertheless suggests the possibility that alternative nucleotide conformations may sometimes be present.ConclusionWe discuss the implications of using our method to discover DNA sequences capable of forming alternative structures. The analyses presented here can be reproduced on any Pacific Biosciences kinetics data for any DNA pattern of interest using an R package that we have made publicly available.

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X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 3%
Norway 1 2%
Unknown 63 95%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 13 20%
Student > Master 13 20%
Researcher 10 15%
Student > Bachelor 6 9%
Professor 5 8%
Other 11 17%
Unknown 8 12%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 24 36%
Biochemistry, Genetics and Molecular Biology 14 21%
Computer Science 7 11%
Medicine and Dentistry 4 6%
Chemistry 3 5%
Other 5 8%
Unknown 9 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 21 September 2019.
All research outputs
#7,325,456
of 26,745,229 outputs
Outputs from BMC Bioinformatics
#2,452
of 7,842 outputs
Outputs of similar age
#88,705
of 365,557 outputs
Outputs of similar age from BMC Bioinformatics
#37
of 130 outputs
Altmetric has tracked 26,745,229 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,842 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has gotten more attention than average, scoring higher than 68% 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 365,557 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 75% of its contemporaries.
We're also able to compare this research output to 130 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 71% of its contemporaries.