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SeqWare Query Engine: storing and searching sequence data in the cloud

Overview of attention for article published in BMC Bioinformatics, January 2010
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

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75 Dimensions

Readers on

mendeley
145 Mendeley
citeulike
8 CiteULike
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Title
SeqWare Query Engine: storing and searching sequence data in the cloud
Published in
BMC Bioinformatics, January 2010
DOI 10.1186/1471-2105-11-s12-s2
Pubmed ID
Authors

Brian D O’Connor, Barry Merriman, Stanley F Nelson

Abstract

Since the introduction of next-generation DNA sequencers the rapid increase in sequencer throughput, and associated drop in costs, has resulted in more than a dozen human genomes being resequenced over the last few years. These efforts are merely a prelude for a future in which genome resequencing will be commonplace for both biomedical research and clinical applications. The dramatic increase in sequencer output strains all facets of computational infrastructure, especially databases and query interfaces. The advent of cloud computing, and a variety of powerful tools designed to process petascale datasets, provide a compelling solution to these ever increasing demands.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 6%
Germany 3 2%
Canada 2 1%
Japan 2 1%
Australia 2 1%
Spain 2 1%
France 2 1%
New Zealand 1 <1%
Iceland 1 <1%
Other 4 3%
Unknown 117 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 40 28%
Student > Ph. D. Student 32 22%
Student > Master 27 19%
Other 9 6%
Professor > Associate Professor 8 6%
Other 26 18%
Unknown 3 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 55 38%
Computer Science 53 37%
Biochemistry, Genetics and Molecular Biology 8 6%
Engineering 6 4%
Medicine and Dentistry 4 3%
Other 12 8%
Unknown 7 5%

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 22 September 2014.
All research outputs
#2,294,594
of 4,507,652 outputs
Outputs from BMC Bioinformatics
#1,825
of 2,646 outputs
Outputs of similar age
#57,406
of 119,036 outputs
Outputs of similar age from BMC Bioinformatics
#81
of 110 outputs
Altmetric has tracked 4,507,652 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,646 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 20th percentile – i.e., 20% 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 119,036 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.