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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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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.

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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%