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A Comprehensive Benchmark Study of Multiple Sequence Alignment Methods: Current Challenges and Future Perspectives

Overview of attention for article published in PLOS ONE, March 2011
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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 (94th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

blogs
1 blog
twitter
3 X users
wikipedia
2 Wikipedia pages
q&a
3 Q&A threads

Citations

dimensions_citation
193 Dimensions

Readers on

mendeley
448 Mendeley
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12 CiteULike
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Title
A Comprehensive Benchmark Study of Multiple Sequence Alignment Methods: Current Challenges and Future Perspectives
Published in
PLOS ONE, March 2011
DOI 10.1371/journal.pone.0018093
Pubmed ID
Authors

Julie D. Thompson, Benjamin Linard, Odile Lecompte, Olivier Poch

Abstract

Multiple comparison or alignmentof protein sequences has become a fundamental tool in many different domains in modern molecular biology, from evolutionary studies to prediction of 2D/3D structure, molecular function and inter-molecular interactions etc. By placing the sequence in the framework of the overall family, multiple alignments can be used to identify conserved features and to highlight differences or specificities. In this paper, we describe a comprehensive evaluation of many of the most popular methods for multiple sequence alignment (MSA), based on a new benchmark test set. The benchmark is designed to represent typical problems encountered when aligning the large protein sequence sets that result from today's high throughput biotechnologies. We show that alignmentmethods have significantly progressed and can now identify most of the shared sequence features that determine the broad molecular function(s) of a protein family, even for divergent sequences. However,we have identified a number of important challenges. First, the locally conserved regions, that reflect functional specificities or that modulate a protein's function in a given cellular context,are less well aligned. Second, motifs in natively disordered regions are often misaligned. Third, the badly predicted or fragmentary protein sequences, which make up a large proportion of today's databases, lead to a significant number of alignment errors. Based on this study, we demonstrate that the existing MSA methods can be exploited in combination to improve alignment accuracy, although novel approaches will still be needed to fully explore the most difficult regions. We then propose knowledge-enabled, dynamic solutions that will hopefully pave the way to enhanced alignment construction and exploitation in future evolutionary systems biology studies.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 448 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 12 3%
United States 9 2%
France 3 <1%
Spain 3 <1%
Canada 3 <1%
Australia 2 <1%
Argentina 2 <1%
Germany 2 <1%
Finland 2 <1%
Other 9 2%
Unknown 401 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 101 23%
Researcher 91 20%
Student > Master 68 15%
Student > Bachelor 58 13%
Student > Doctoral Student 15 3%
Other 54 12%
Unknown 61 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 185 41%
Biochemistry, Genetics and Molecular Biology 84 19%
Computer Science 54 12%
Immunology and Microbiology 9 2%
Chemistry 7 2%
Other 39 9%
Unknown 70 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 December 2020.
All research outputs
#1,663,264
of 24,654,416 outputs
Outputs from PLOS ONE
#20,774
of 213,242 outputs
Outputs of similar age
#6,653
of 113,657 outputs
Outputs of similar age from PLOS ONE
#155
of 1,463 outputs
Altmetric has tracked 24,654,416 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 213,242 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has done particularly well, scoring higher than 90% 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 113,657 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 94% of its contemporaries.
We're also able to compare this research output to 1,463 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.