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Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

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

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
1 tweeter
wikipedia
1 Wikipedia page

Citations

dimensions_citation
91 Dimensions

Readers on

mendeley
52 Mendeley
citeulike
2 CiteULike
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Title
Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information
Published in
BMC Bioinformatics, June 2007
DOI 10.1186/1471-2105-8-201
Pubmed ID
Authors

Gianluca Pollastri, Alberto JM Martin, Catherine Mooney, Alessandro Vullo

Abstract

Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio.

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

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 2%
Spain 1 2%
United States 1 2%
Unknown 49 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 19%
Student > Ph. D. Student 9 17%
Student > Master 8 15%
Student > Bachelor 7 13%
Lecturer 5 10%
Other 9 17%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 35%
Computer Science 12 23%
Biochemistry, Genetics and Molecular Biology 7 13%
Medicine and Dentistry 2 4%
Engineering 2 4%
Other 3 6%
Unknown 8 15%

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 29 April 2015.
All research outputs
#6,039,387
of 19,985,377 outputs
Outputs from BMC Bioinformatics
#2,449
of 6,707 outputs
Outputs of similar age
#50,834
of 170,871 outputs
Outputs of similar age from BMC Bioinformatics
#16
of 33 outputs
Altmetric has tracked 19,985,377 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 6,707 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 61% 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 170,871 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 33 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 54% of its contemporaries.