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Enrichment of Triticum aestivum gene annotations using ortholog cliques and gene ontologies in other plants

Overview of attention for article published in BMC Genomics, April 2015
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  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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5 tweeters

Citations

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6 Dimensions

Readers on

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19 Mendeley
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1 CiteULike
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Title
Enrichment of Triticum aestivum gene annotations using ortholog cliques and gene ontologies in other plants
Published in
BMC Genomics, April 2015
DOI 10.1186/s12864-015-1496-2
Pubmed ID
Authors

Dan Tulpan, Serge Leger, Alain Tchagang, Youlian Pan

Abstract

While the gargantuan multi-nation effort of sequencing T. aestivum gets close to completion, the annotation process for the vast number of wheat genes and proteins is in its infancy. Previous experimental studies carried out on model plant organisms such as A. thaliana and O. sativa provide a plethora of gene annotations that can be used as potential starting points for wheat gene annotations, proven that solid cross-species gene-to-gene and protein-to-protein correspondences are provided. DNA and protein sequences and corresponding annotations for T. aestivum and 9 other plant species were collected from Ensembl Plants release 22 and curated. Cliques of predicted 1-to-1 orthologs were identified and an annotation enrichment model was defined based on existing gene-GO term associations and phylogenetic relationships among wheat and 9 other plant species. A total of 13 cliques of size 10 were identified, which represent putative functionally equivalent genes and proteins in the 10 plant species. Eighty-five new and more specific GO terms were associated with wheat genes in the 13 cliques of size 10, which represent a 65% increase compared with the previously 130 known GO terms. Similar expression patterns for 4 genes from Arabidopsis, barley, maize and rice in cliques of size 10 provide experimental evidence to support our model. Overall, based on clique size equal or larger than 3, our model enriched the existing gene-GO term associations for 7,838 (8%) wheat genes, of which 2,139 had no previous annotation. Our novel comparative genomics approach enriches existing T. aestivum gene annotations based on cliques of predicted 1-to-1 orthologs, phylogenetic relationships and existing gene ontologies from 9 other plant species.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 26%
Student > Ph. D. Student 4 21%
Student > Doctoral Student 3 16%
Student > Master 2 11%
Student > Bachelor 1 5%
Other 1 5%
Unknown 3 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 58%
Computer Science 3 16%
Biochemistry, Genetics and Molecular Biology 2 11%
Linguistics 1 5%
Unknown 2 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 26 January 2016.
All research outputs
#5,703,161
of 11,346,162 outputs
Outputs from BMC Genomics
#2,676
of 6,796 outputs
Outputs of similar age
#76,621
of 213,652 outputs
Outputs of similar age from BMC Genomics
#114
of 225 outputs
Altmetric has tracked 11,346,162 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,796 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 60% 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 213,652 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 63% of its contemporaries.
We're also able to compare this research output to 225 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.