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Minimus: a fast, lightweight genome assembler

Overview of attention for article published in BMC Bioinformatics, January 2007
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

twitter
3 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
304 Dimensions

Readers on

mendeley
345 Mendeley
citeulike
12 CiteULike
connotea
6 Connotea
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Title
Minimus: a fast, lightweight genome assembler
Published in
BMC Bioinformatics, January 2007
DOI 10.1186/1471-2105-8-64
Pubmed ID
Authors

Daniel D Sommer, Arthur L Delcher, Steven L Salzberg, Mihai Pop

Abstract

Genome assemblers have grown very large and complex in response to the need for algorithms to handle the challenges of large whole-genome sequencing projects. Many of the most common uses of assemblers, however, are best served by a simpler type of assembler that requires fewer software components, uses less memory, and is far easier to install and run. We have developed the Minimus assembler to address these issues, and tested it on a range of assembly problems. We show that Minimus performs well on several small assembly tasks, including the assembly of viral genomes, individual genes, and BAC clones. In addition, we evaluate Minimus' performance in assembling bacterial genomes in order to assess its suitability as a component of a larger assembly pipeline. We show that, unlike other software currently used for these tasks, Minimus produces significantly fewer assembly errors, at the cost of generating a more fragmented assembly. We find that for small genomes and other small assembly tasks, Minimus is faster and far more flexible than existing tools. Due to its small size and modular design Minimus is perfectly suited to be a component of complex assembly pipelines. Minimus is released as an open-source software project and the code is available as part of the AMOS project at Sourceforge.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 345 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 17 5%
Brazil 8 2%
Germany 7 2%
Canada 2 <1%
Spain 2 <1%
Mexico 2 <1%
Sweden 2 <1%
United Kingdom 2 <1%
New Zealand 1 <1%
Other 8 2%
Unknown 294 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 97 28%
Student > Ph. D. Student 87 25%
Student > Master 35 10%
Professor > Associate Professor 29 8%
Student > Bachelor 22 6%
Other 58 17%
Unknown 17 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 214 62%
Biochemistry, Genetics and Molecular Biology 34 10%
Computer Science 33 10%
Environmental Science 11 3%
Immunology and Microbiology 4 1%
Other 16 5%
Unknown 33 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 24 April 2013.
All research outputs
#2,505,600
of 11,194,639 outputs
Outputs from BMC Bioinformatics
#1,201
of 4,189 outputs
Outputs of similar age
#28,491
of 128,860 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 124 outputs
Altmetric has tracked 11,194,639 research outputs across all sources so far. Compared to these this one has done well and is in the 77th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,189 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 70% 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 128,860 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 77% of its contemporaries.
We're also able to compare this research output to 124 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.