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Combined Evidence Annotation of Transposable Elements in Genome Sequences

Overview of attention for article published in PLoS Computational Biology, July 2005
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

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2 X users
wikipedia
2 Wikipedia pages

Citations

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349 Dimensions

Readers on

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333 Mendeley
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20 CiteULike
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5 Connotea
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Title
Combined Evidence Annotation of Transposable Elements in Genome Sequences
Published in
PLoS Computational Biology, July 2005
DOI 10.1371/journal.pcbi.0010022
Pubmed ID
Authors

Hadi Quesneville, Casey M Bergman, Olivier Andrieu, Delphine Autard, Danielle Nouaud, Michael Ashburner, Dominique Anxolabehere

Abstract

Transposable elements (TEs) are mobile, repetitive sequences that make up significant fractions of metazoan genomes. Despite their near ubiquity and importance in genome and chromosome biology, most efforts to annotate TEs in genome sequences rely on the results of a single computational program, RepeatMasker. In contrast, recent advances in gene annotation indicate that high-quality gene models can be produced from combining multiple independent sources of computational evidence. To elevate the quality of TE annotations to a level comparable to that of gene models, we have developed a combined evidence-model TE annotation pipeline, analogous to systems used for gene annotation, by integrating results from multiple homology-based and de novo TE identification methods. As proof of principle, we have annotated "TE models" in Drosophila melanogaster Release 4 genomic sequences using the combined computational evidence derived from RepeatMasker, BLASTER, TBLASTX, all-by-all BLASTN, RECON, TE-HMM and the previous Release 3.1 annotation. Our system is designed for use with the Apollo genome annotation tool, allowing automatic results to be curated manually to produce reliable annotations. The euchromatic TE fraction of D. melanogaster is now estimated at 5.3% (cf. 3.86% in Release 3.1), and we found a substantially higher number of TEs (n = 6,013) than previously identified (n = 1,572). Most of the new TEs derive from small fragments of a few hundred nucleotides long and highly abundant families not previously annotated (e.g., INE-1). We also estimated that 518 TE copies (8.6%) are inserted into at least one other TE, forming a nest of elements. The pipeline allows rapid and thorough annotation of even the most complex TE models, including highly deleted and/or nested elements such as those often found in heterochromatic sequences. Our pipeline can be easily adapted to other genome sequences, such as those of the D. melanogaster heterochromatin or other species in the genus Drosophila.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 333 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 3%
Brazil 7 2%
United Kingdom 7 2%
France 5 2%
Germany 3 <1%
Canada 3 <1%
New Zealand 2 <1%
Argentina 2 <1%
Norway 1 <1%
Other 7 2%
Unknown 285 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 95 29%
Student > Ph. D. Student 89 27%
Student > Master 32 10%
Student > Bachelor 22 7%
Professor > Associate Professor 21 6%
Other 51 15%
Unknown 23 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 208 62%
Biochemistry, Genetics and Molecular Biology 44 13%
Computer Science 28 8%
Engineering 7 2%
Environmental Science 4 1%
Other 12 4%
Unknown 30 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 11 October 2016.
All research outputs
#7,363,939
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#4,996
of 8,964 outputs
Outputs of similar age
#22,182
of 68,872 outputs
Outputs of similar age from PLoS Computational Biology
#7
of 17 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 43rd percentile – i.e., 43% 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 68,872 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
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 has gotten more attention than average, scoring higher than 52% of its contemporaries.