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Partially local three-way alignments and the sequence signatures of mitochondrial genome rearrangements

Overview of attention for article published in Algorithms for Molecular Biology, August 2017
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Title
Partially local three-way alignments and the sequence signatures of mitochondrial genome rearrangements
Published in
Algorithms for Molecular Biology, August 2017
DOI 10.1186/s13015-017-0113-0
Pubmed ID
Authors

Marwa Al Arab, Matthias Bernt, Christian Höner zu Siederdissen, Kifah Tout, Peter F. Stadler

Abstract

Genomic DNA frequently undergoes rearrangement of the gene order that can be localized by comparing the two DNA sequences. In mitochondrial genomes different mechanisms are likely at work, at least some of which involve the duplication of sequence around the location of the apparent breakpoints. We hypothesize that these different mechanisms of genome rearrangement leave distinctive sequence footprints. In order to study such effects it is important to locate the breakpoint positions with precision. We define a partially local sequence alignment problem that assumes that following a rearrangement of a sequence F, two fragments L, and R are produced that may exactly fit together to match F, leave a gap of deleted DNA between L and R, or overlap with each other. We show that this alignment problem can be solved by dynamic programming in cubic space and time. We apply the new method to evaluate rearrangements of animal mitogenomes and find that a surprisingly large fraction of these events involved local sequence duplications. The partially local sequence alignment method is an effective way to investigate the mechanism of genomic rearrangement events. While applied here only to mitogenomes there is no reason why the method could not be used to also consider rearrangements in nuclear genomes.

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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 45%
Unspecified 2 18%
Student > Doctoral Student 1 9%
Student > Ph. D. Student 1 9%
Professor > Associate Professor 1 9%
Other 1 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 27%
Unspecified 2 18%
Biochemistry, Genetics and Molecular Biology 2 18%
Computer Science 2 18%
Environmental Science 1 9%
Other 1 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 31 August 2017.
All research outputs
#9,336,011
of 11,682,907 outputs
Outputs from Algorithms for Molecular Biology
#118
of 180 outputs
Outputs of similar age
#193,290
of 263,777 outputs
Outputs of similar age from Algorithms for Molecular Biology
#4
of 8 outputs
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So far Altmetric has tracked 180 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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