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Screening synteny blocks in pairwise genome comparisons through integer programming

Overview of attention for article published in BMC Bioinformatics, April 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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1 blog
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1 X user

Citations

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130 Dimensions

Readers on

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120 Mendeley
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5 CiteULike
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Title
Screening synteny blocks in pairwise genome comparisons through integer programming
Published in
BMC Bioinformatics, April 2011
DOI 10.1186/1471-2105-12-102
Pubmed ID
Authors

Haibao Tang, Eric Lyons, Brent Pedersen, James C Schnable, Andrew H Paterson, Michael Freeling

Abstract

It is difficult to accurately interpret chromosomal correspondences such as true orthology and paralogy due to significant divergence of genomes from a common ancestor. Analyses are particularly problematic among lineages that have repeatedly experienced whole genome duplication (WGD) events. To compare multiple "subgenomes" derived from genome duplications, we need to relax the traditional requirements of "one-to-one" syntenic matchings of genomic regions in order to reflect "one-to-many" or more generally "many-to-many" matchings. However this relaxation may result in the identification of synteny blocks that are derived from ancient shared WGDs that are not of interest. For many downstream analyses, we need to eliminate weak, low scoring alignments from pairwise genome comparisons. Our goal is to objectively select subset of synteny blocks whose total scores are maximized while respecting the duplication history of the genomes in comparison. We call this "quota-based" screening of synteny blocks in order to appropriately fill a quota of syntenic relationships within one genome or between two genomes having WGD events.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Germany 2 2%
Belgium 2 2%
Australia 1 <1%
Brazil 1 <1%
Sweden 1 <1%
Chile 1 <1%
Norway 1 <1%
Taiwan 1 <1%
Other 2 2%
Unknown 103 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 24%
Student > Ph. D. Student 27 23%
Student > Master 15 13%
Student > Bachelor 9 8%
Other 6 5%
Other 20 17%
Unknown 14 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 76 63%
Biochemistry, Genetics and Molecular Biology 16 13%
Computer Science 2 2%
Mathematics 1 <1%
Nursing and Health Professions 1 <1%
Other 4 3%
Unknown 20 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 21 June 2014.
All research outputs
#3,145,458
of 22,649,029 outputs
Outputs from BMC Bioinformatics
#1,153
of 7,234 outputs
Outputs of similar age
#14,878
of 109,232 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 65 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,234 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 84% of its peers.
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 109,232 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.