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OMGene: mutual improvement of gene models through optimisation of evolutionary conservation

Overview of attention for article published in BMC Genomics, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Title
OMGene: mutual improvement of gene models through optimisation of evolutionary conservation
Published in
BMC Genomics, April 2018
DOI 10.1186/s12864-018-4704-z
Pubmed ID
Authors

Michael P. Dunne, Steven Kelly

Abstract

The accurate determination of the genomic coordinates for a given gene - its gene model - is of vital importance to the utility of its annotation, and the accuracy of bioinformatic analyses derived from it. Currently-available methods of computational gene prediction, while on the whole successful, frequently disagree on the model for a given predicted gene, with some or all of the variant gene models often failing to match the biologically observed structure. Many prediction methods can be bolstered by using experimental data such as RNA-seq. However, these resources are not always available, and rarely give a comprehensive portrait of an organism's transcriptome due to temporal and tissue-specific expression profiles. Orthology between genes provides evolutionary evidence to guide the construction of gene models. OMGene (Optimise My Gene) aims to improve gene model accuracy in the absence of experimental data by optimising the consistency of multiple sequence alignments of orthologous genes from multiple species. Using RNA-seq data sets from plants, mammals, and fungi, considering intron/exon junction representation and exon coverage, and assessing the intra-orthogroup consistency of subcellular localisation predictions, we demonstrate the utility of OMGene for improving gene models in annotated genomes. We show that significant improvements in the accuracy of gene model annotations can be made, both in established and in de novo annotated genomes, by leveraging information from multiple species.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 24%
Student > Ph. D. Student 3 14%
Student > Doctoral Student 2 10%
Student > Bachelor 2 10%
Student > Master 2 10%
Other 4 19%
Unknown 3 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 43%
Biochemistry, Genetics and Molecular Biology 7 33%
Mathematics 1 5%
Computer Science 1 5%
Psychology 1 5%
Other 0 0%
Unknown 2 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 05 April 2019.
All research outputs
#3,862,191
of 23,577,654 outputs
Outputs from BMC Genomics
#1,507
of 10,777 outputs
Outputs of similar age
#74,643
of 327,649 outputs
Outputs of similar age from BMC Genomics
#44
of 238 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,777 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 86% 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 327,649 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 77% of its contemporaries.
We're also able to compare this research output to 238 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.