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Whole genome phylogenies for multiple Drosophila species

Overview of attention for article published in BMC Research Notes, December 2012
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Title
Whole genome phylogenies for multiple Drosophila species
Published in
BMC Research Notes, December 2012
DOI 10.1186/1756-0500-5-670
Pubmed ID
Authors

Arun Seetharam, Gary W Stuart

Abstract

Reconstructing the evolutionary history of organisms using traditional phylogenetic methods may suffer from inaccurate sequence alignment. An alternative approach, particularly effective when whole genome sequences are available, is to employ methods that don't use explicit sequence alignments. We extend a novel phylogenetic method based on Singular Value Decomposition (SVD) to reconstruct the phylogeny of 12 sequenced Drosophila species. SVD analysis provides accurate comparisons for a high fraction of sequences within whole genomes without the prior identification of orthologs or homologous sites. With this method all protein sequences are converted to peptide frequency vectors within a matrix that is decomposed to provide simplified vector representations for each protein of the genome in a reduced dimensional space. These vectors are summed together to provide a vector representation for each species, and the angle between these vectors provides distance measures that are used to construct species trees.

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

Geographical breakdown

Country Count As %
Brazil 2 7%
Unknown 27 93%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 21%
Student > Ph. D. Student 5 17%
Researcher 4 14%
Student > Master 4 14%
Professor 1 3%
Other 2 7%
Unknown 7 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 45%
Biochemistry, Genetics and Molecular Biology 4 14%
Computer Science 2 7%
Psychology 1 3%
Medicine and Dentistry 1 3%
Other 0 0%
Unknown 8 28%
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 12 December 2012.
All research outputs
#15,258,711
of 22,689,790 outputs
Outputs from BMC Research Notes
#2,310
of 4,254 outputs
Outputs of similar age
#179,369
of 277,752 outputs
Outputs of similar age from BMC Research Notes
#45
of 72 outputs
Altmetric has tracked 22,689,790 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 33rd percentile – i.e., 33% 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 277,752 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 72 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.