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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, July 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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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1 policy source
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16 X users
weibo
1 weibo user

Citations

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12 Dimensions

Readers on

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

Basil Britto 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Netherlands 1 2%
South Africa 1 2%
Japan 1 2%
United States 1 2%
Unknown 45 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Student > Bachelor 6 12%
Student > Master 6 12%
Researcher 6 12%
Student > Doctoral Student 4 8%
Other 9 18%
Unknown 7 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 38%
Biochemistry, Genetics and Molecular Biology 10 20%
Computer Science 4 8%
Immunology and Microbiology 3 6%
Medicine and Dentistry 3 6%
Other 2 4%
Unknown 9 18%
Attention Score in Context

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
#2,535,092
of 24,885,505 outputs
Outputs from BMC Research Notes
#334
of 4,470 outputs
Outputs of similar age
#24,851
of 234,248 outputs
Outputs of similar age from BMC Research Notes
#19
of 142 outputs
Altmetric has tracked 24,885,505 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,470 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done particularly well, scoring higher than 92% 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 234,248 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.