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Assessing the efficiency of multiple sequence alignment programs

Overview of attention for article published in Algorithms for Molecular Biology, March 2014
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About this Attention Score

  • Among the highest-scoring outputs from this source (#44 of 195)
  • Good Attention Score compared to outputs of the same age (75th percentile)

Mentioned by

twitter
3 tweeters
wikipedia
1 Wikipedia page

Citations

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47 Dimensions

Readers on

mendeley
303 Mendeley
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Title
Assessing the efficiency of multiple sequence alignment programs
Published in
Algorithms for Molecular Biology, March 2014
DOI 10.1186/1748-7188-9-4
Pubmed ID
Authors

Fabiano Sviatopolk-Mirsky Pais, Patrícia de Ruy, Guilherme Oliveira, Roney Coimbra

Abstract

Multiple sequence alignment (MSA) is an extremely useful tool for molecular and evolutionary biology and there are several programs and algorithms available for this purpose. Although previous studies have compared the alignment accuracy of different MSA programs, their computational time and memory usage have not been systematically evaluated. Given the unprecedented amount of data produced by next generation deep sequencing platforms, and increasing demand for large-scale data analysis, it is imperative to optimize the application of software. Therefore, a balance between alignment accuracy and computational cost has become a critical indicator of the most suitable MSA program. We compared both accuracy and cost of nine popular MSA programs, namely CLUSTALW, CLUSTAL OMEGA, DIALIGN-TX, MAFFT, MUSCLE, POA, Probalign, Probcons and T-Coffee, against the benchmark alignment dataset BAliBASE and discuss the relevance of some implementations embedded in each program's algorithm. Accuracy of alignment was calculated with the two standard scoring functions provided by BAliBASE, the sum-of-pairs and total-column scores, and computational costs were determined by collecting peak memory usage and time of execution.

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

Geographical breakdown

Country Count As %
United Kingdom 3 <1%
Spain 2 <1%
Colombia 2 <1%
Chile 2 <1%
Australia 2 <1%
Czechia 1 <1%
Finland 1 <1%
Brazil 1 <1%
Germany 1 <1%
Other 6 2%
Unknown 282 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 74 24%
Student > Master 63 21%
Student > Bachelor 61 20%
Researcher 44 15%
Student > Doctoral Student 16 5%
Other 29 10%
Unknown 16 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 144 48%
Biochemistry, Genetics and Molecular Biology 84 28%
Computer Science 20 7%
Medicine and Dentistry 6 2%
Engineering 6 2%
Other 23 8%
Unknown 20 7%

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 24 April 2018.
All research outputs
#3,288,758
of 12,846,518 outputs
Outputs from Algorithms for Molecular Biology
#44
of 195 outputs
Outputs of similar age
#45,439
of 188,865 outputs
Outputs of similar age from Algorithms for Molecular Biology
#2
of 3 outputs
Altmetric has tracked 12,846,518 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 195 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done well, scoring higher than 77% 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 188,865 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 75% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.