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Drug target prediction and prioritization: using orthology to predict essentiality in parasite genomes

Overview of attention for article published in BMC Genomics, April 2010
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1 Wikipedia page

Citations

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77 Dimensions

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85 Mendeley
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4 CiteULike
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Title
Drug target prediction and prioritization: using orthology to predict essentiality in parasite genomes
Published in
BMC Genomics, April 2010
DOI 10.1186/1471-2164-11-222
Pubmed ID
Authors

Maria A Doyle, Robin B Gasser, Ben J Woodcroft, Ross S Hall, Stuart A Ralph

Abstract

New drug targets are urgently needed for parasites of socio-economic importance. Genes that are essential for parasite survival are highly desirable targets, but information on these genes is lacking, as gene knockouts or knockdowns are difficult to perform in many species of parasites. We examined the applicability of large-scale essentiality information from four model eukaryotes, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus and Saccharomyces cerevisiae, to discover essential genes in each of their genomes. Parasite genes that lack orthologues in their host are desirable as selective targets, so we also examined prediction of essential genes within this subset.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 1%
Spain 1 1%
Poland 1 1%
Kenya 1 1%
Unknown 81 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 24%
Student > Master 16 19%
Researcher 15 18%
Student > Bachelor 5 6%
Professor > Associate Professor 5 6%
Other 12 14%
Unknown 12 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 41%
Biochemistry, Genetics and Molecular Biology 15 18%
Computer Science 5 6%
Veterinary Science and Veterinary Medicine 2 2%
Engineering 2 2%
Other 9 11%
Unknown 17 20%
Attention Score in Context

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 24 January 2011.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Genomics
#3,597
of 10,647 outputs
Outputs of similar age
#34,635
of 95,277 outputs
Outputs of similar age from BMC Genomics
#15
of 44 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,647 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 59% 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 95,277 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.