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Methods for detection of horizontal transfer of transposable elements in complete genomes

Overview of attention for article published in Genetics and Molecular Biology, December 2012
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Title
Methods for detection of horizontal transfer of transposable elements in complete genomes
Published in
Genetics and Molecular Biology, December 2012
DOI 10.1590/s1415-47572012000600024
Pubmed ID
Authors

Marcos Oliveira de Carvalho, Elgion L.S. Loreto

Abstract

Recent advances in nucleic acid sequencing technology are creating a diverse landscape for the analysis of horizontal transfer in complete genomes. Previously limited to prokaryotes, the availability of complete genomes from close eukaryotic species presents an opportunity to validate hypotheses about the patterns of evolution and mechanisms that drive horizontal transfer. Many of those methods can be transported from methods previously used in prokaryotic genomes, as the assumptions for horizontal transfer can be interpreted as the same. Some methods, however, require a complete adaptation, while others need refinements in sensitivity and specificity to deal with the huge datasets generated from next-generation sequencing technologies. Here we list the types of methods used for horizontal transfer detection, as well as theirs strengths and weakness.

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X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 4 6%
Germany 2 3%
France 1 2%
United Kingdom 1 2%
Canada 1 2%
Unknown 53 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 27%
Student > Ph. D. Student 14 23%
Student > Master 10 16%
Student > Bachelor 6 10%
Student > Doctoral Student 3 5%
Other 9 15%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 50%
Biochemistry, Genetics and Molecular Biology 16 26%
Environmental Science 4 6%
Computer Science 3 5%
Mathematics 1 2%
Other 2 3%
Unknown 5 8%
Attention Score in Context

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 13 March 2013.
All research outputs
#17,285,036
of 25,371,288 outputs
Outputs from Genetics and Molecular Biology
#408
of 771 outputs
Outputs of similar age
#193,421
of 288,525 outputs
Outputs of similar age from Genetics and Molecular Biology
#13
of 17 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 771 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.