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Employing whole genome mapping for optimal de novo assembly of bacterial genomes

Overview of attention for article published in BMC Research Notes, January 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

twitter
24 tweeters
weibo
1 weibo user

Citations

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10 Dimensions

Readers on

mendeley
40 Mendeley
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Title
Employing whole genome mapping for optimal de novo assembly of bacterial genomes
Published in
BMC Research Notes, January 2014
DOI 10.1186/1756-0500-7-484
Pubmed ID
Authors

Basil Xavier, Julia Sabirova, Moons Pieter, Jean-Pierre Hernalsteens, Henri de Greve, Herman Goossens, Surbhi Malhotra-Kumar

Abstract

De novo genome assembly can be challenging due to inherent properties of the reads, even when using current state-of-the-art assembly tools based on de Bruijn graphs. Often users are not bio-informaticians and, in a black box approach, utilise assembly parameters such as contig length and N50 to generate whole genome sequences, potentially resulting in mis-assemblies.

Twitter Demographics

The data shown below were collected from the profiles of 24 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
South Africa 1 3%
Japan 1 3%
United States 1 3%
Netherlands 1 3%
Unknown 35 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 30%
Student > Bachelor 7 18%
Researcher 6 15%
Student > Postgraduate 4 10%
Unspecified 3 8%
Other 8 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 48%
Unspecified 5 13%
Biochemistry, Genetics and Molecular Biology 5 13%
Computer Science 3 8%
Medicine and Dentistry 3 8%
Other 5 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 20 November 2017.
All research outputs
#982,976
of 12,519,627 outputs
Outputs from BMC Research Notes
#142
of 2,804 outputs
Outputs of similar age
#18,233
of 193,110 outputs
Outputs of similar age from BMC Research Notes
#3
of 20 outputs
Altmetric has tracked 12,519,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,804 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 95% 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 193,110 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 20 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 70% of its contemporaries.