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LTRtype, an Efficient Tool to Characterize Structurally Complex LTR Retrotransposons and Nested Insertions on Genomes

Overview of attention for article published in Frontiers in Plant Science, April 2017
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Title
LTRtype, an Efficient Tool to Characterize Structurally Complex LTR Retrotransposons and Nested Insertions on Genomes
Published in
Frontiers in Plant Science, April 2017
DOI 10.3389/fpls.2017.00402
Pubmed ID
Authors

Fan-Chun Zeng, You-Jie Zhao, Que-Jie Zhang, Li-Zhi Gao

Abstract

The amplification and recombination of long terminal repeat (LTR) retrotransposons have proven to determine the size, organization, function, and evolution of most host genomes, especially very large plant genomes. However, the limitation of tools for an efficient discovery of structural complexity of LTR retrotransposons and the nested insertions is a great challenge to confront ever-growing amount of genomic sequences for many organisms. Here we developed a novel software, called as LTRtype, to characterize different types of structurally complex LTR retrotransposon elements as well as nested events. This system is capable of rapidly scanning large-scale genomic sequences and appropriately characterizing the five complex types of LTR retrotransposon elements. After testing on the Arabidopsis thaliana genome, we found that this program is able to properly annotate a large number of structurally complex elements as well as the nested insertions. Thus, LTRtype can be employed as an automatic and efficient tool that will help to reconstruct the evolutionary history of LTR retrotransposons and better understand the evolution of host genomes. LTRtype is publicly available at: http://www.plantkingdomgdb.com/LTRtype/index.html.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
Canada 1 3%
Unknown 38 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 33%
Student > Ph. D. Student 9 23%
Student > Bachelor 4 10%
Student > Master 3 8%
Lecturer > Senior Lecturer 1 3%
Other 3 8%
Unknown 7 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 40%
Biochemistry, Genetics and Molecular Biology 8 20%
Computer Science 3 8%
Medicine and Dentistry 2 5%
Engineering 2 5%
Other 0 0%
Unknown 9 23%
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 20 April 2017.
All research outputs
#18,349,015
of 23,577,654 outputs
Outputs from Frontiers in Plant Science
#12,815
of 21,632 outputs
Outputs of similar age
#222,211
of 310,178 outputs
Outputs of similar age from Frontiers in Plant Science
#379
of 552 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 21,632 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 31st percentile – i.e., 31% 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 310,178 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 552 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.