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MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue-residue contacts

Overview of attention for article published in BMC Bioinformatics, December 2011
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1 tweeter

Citations

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24 Dimensions

Readers on

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59 Mendeley
citeulike
6 CiteULike
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Title
MSACompro: protein multiple sequence alignment using predicted secondary structure, solvent accessibility, and residue-residue contacts
Published in
BMC Bioinformatics, December 2011
DOI 10.1186/1471-2105-12-472
Pubmed ID
Authors

Xin Deng, Jianlin Cheng

Abstract

Multiple Sequence Alignment (MSA) is a basic tool for bioinformatics research and analysis. It has been used essentially in almost all bioinformatics tasks such as protein structure modeling, gene and protein function prediction, DNA motif recognition, and phylogenetic analysis. Therefore, improving the accuracy of multiple sequence alignment is important for advancing many bioinformatics fields.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 3 5%
Australia 1 2%
Cuba 1 2%
Sweden 1 2%
United Kingdom 1 2%
Spain 1 2%
United States 1 2%
Poland 1 2%
Unknown 49 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 34%
Researcher 10 17%
Student > Master 7 12%
Student > Bachelor 6 10%
Professor > Associate Professor 4 7%
Other 10 17%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 41%
Computer Science 13 22%
Biochemistry, Genetics and Molecular Biology 7 12%
Chemistry 4 7%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Other 5 8%
Unknown 4 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 15 December 2011.
All research outputs
#9,906,144
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,816
of 4,576 outputs
Outputs of similar age
#156,767
of 218,790 outputs
Outputs of similar age from BMC Bioinformatics
#149
of 181 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 218,790 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 181 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.