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WebMGA: a customizable web server for fast metagenomic sequence analysis

Overview of attention for article published in BMC Genomics, September 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
2 tweeters
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
530 Dimensions

Readers on

mendeley
424 Mendeley
citeulike
9 CiteULike
connotea
1 Connotea
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Title
WebMGA: a customizable web server for fast metagenomic sequence analysis
Published in
BMC Genomics, September 2011
DOI 10.1186/1471-2164-12-444
Pubmed ID
Authors

Sitao Wu, Zhengwei Zhu, Liming Fu, Beifang Niu, Weizhong Li

Abstract

The new field of metagenomics studies microorganism communities by culture-independent sequencing. With the advances in next-generation sequencing techniques, researchers are facing tremendous challenges in metagenomic data analysis due to huge quantity and high complexity of sequence data. Analyzing large datasets is extremely time-consuming; also metagenomic annotation involves a wide range of computational tools, which are difficult to be installed and maintained by common users. The tools provided by the few available web servers are also limited and have various constraints such as login requirement, long waiting time, inability to configure pipelines etc.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 424 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 1%
Brazil 4 <1%
Italy 2 <1%
Canada 2 <1%
Spain 2 <1%
Denmark 2 <1%
Germany 2 <1%
South Africa 2 <1%
Sweden 1 <1%
Other 11 3%
Unknown 391 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 99 23%
Researcher 81 19%
Student > Master 59 14%
Student > Doctoral Student 28 7%
Student > Bachelor 25 6%
Other 74 17%
Unknown 58 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 211 50%
Biochemistry, Genetics and Molecular Biology 75 18%
Immunology and Microbiology 15 4%
Computer Science 11 3%
Environmental Science 9 2%
Other 29 7%
Unknown 74 17%

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 13 November 2019.
All research outputs
#6,374,317
of 22,651,245 outputs
Outputs from BMC Genomics
#2,862
of 10,605 outputs
Outputs of similar age
#36,565
of 125,706 outputs
Outputs of similar age from BMC Genomics
#25
of 85 outputs
Altmetric has tracked 22,651,245 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 10,605 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 71% 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 125,706 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 68% of its contemporaries.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.