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Parallel-META: efficient metagenomic data analysis based on high-performance computation

Overview of attention for article published in BMC Systems Biology, July 2012
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
31 Dimensions

Readers on

mendeley
82 Mendeley
citeulike
3 CiteULike
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Title
Parallel-META: efficient metagenomic data analysis based on high-performance computation
Published in
BMC Systems Biology, July 2012
DOI 10.1186/1752-0509-6-s1-s16
Pubmed ID
Authors

Xiaoquan Su, Jian Xu, Kang Ning

Abstract

Metagenomics method directly sequences and analyses genome information from microbial communities. There are usually more than hundreds of genomes from different microbial species in the same community, and the main computational tasks for metagenomic data analyses include taxonomical and functional component examination of all genomes in the microbial community. Metagenomic data analysis is both data- and computation- intensive, which requires extensive computational power. Most of the current metagenomic data analysis softwares were designed to be used on a single computer or single computer clusters, which could not match with the fast increasing number of large metagenomic projects' computational requirements. Therefore, advanced computational methods and pipelines have to be developed to cope with such need for efficient analyses.

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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 3 4%
United Kingdom 2 2%
Poland 2 2%
United States 2 2%
Estonia 2 2%
Sweden 1 1%
Colombia 1 1%
Belgium 1 1%
Spain 1 1%
Other 0 0%
Unknown 67 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 37%
Student > Ph. D. Student 16 20%
Student > Master 13 16%
Student > Bachelor 6 7%
Student > Doctoral Student 5 6%
Other 11 13%
Unknown 1 1%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 59%
Biochemistry, Genetics and Molecular Biology 11 13%
Computer Science 10 12%
Environmental Science 4 5%
Chemical Engineering 1 1%
Other 5 6%
Unknown 3 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 19 October 2012.
All research outputs
#6,542,268
of 20,419,783 outputs
Outputs from BMC Systems Biology
#301
of 1,136 outputs
Outputs of similar age
#46,011
of 141,094 outputs
Outputs of similar age from BMC Systems Biology
#3
of 19 outputs
Altmetric has tracked 20,419,783 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,136 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 73% 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 141,094 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 67% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.