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Improved functional prediction of proteins by learning kernel combinations in multilabel settings

Overview of attention for article published in BMC Bioinformatics, May 2007
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1 X user

Citations

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21 Dimensions

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16 Mendeley
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4 CiteULike
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Title
Improved functional prediction of proteins by learning kernel combinations in multilabel settings
Published in
BMC Bioinformatics, May 2007
DOI 10.1186/1471-2105-8-s2-s12
Pubmed ID
Authors

Volker Roth, Bernd Fischer

Abstract

We develop a probabilistic model for combining kernel matrices to predict the function of proteins. It extends previous approaches in that it can handle multiple labels which naturally appear in the context of protein function.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 31%
Student > Bachelor 3 19%
Student > Master 3 19%
Researcher 2 13%
Professor 1 6%
Other 0 0%
Unknown 2 13%
Readers by discipline Count As %
Computer Science 11 69%
Agricultural and Biological Sciences 1 6%
Decision Sciences 1 6%
Engineering 1 6%
Unknown 2 13%
Attention Score in Context

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 17 October 2014.
All research outputs
#18,380,628
of 22,766,595 outputs
Outputs from BMC Bioinformatics
#6,307
of 7,273 outputs
Outputs of similar age
#67,318
of 72,186 outputs
Outputs of similar age from BMC Bioinformatics
#38
of 40 outputs
Altmetric has tracked 22,766,595 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 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 72,186 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.