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NOXclass: prediction of protein-protein interaction types

Overview of attention for article published in BMC Bioinformatics, January 2006
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Mentioned by

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1 Q&A thread

Citations

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174 Dimensions

Readers on

mendeley
83 Mendeley
citeulike
6 CiteULike
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3 Connotea
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Title
NOXclass: prediction of protein-protein interaction types
Published in
BMC Bioinformatics, January 2006
DOI 10.1186/1471-2105-7-27
Pubmed ID
Authors

Hongbo Zhu, Francisco S Domingues, Ingolf Sommer, Thomas Lengauer

Abstract

Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available.

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Brazil 1 1%
Unknown 81 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 7%
Student > Ph. D. Student 3 4%
Student > Bachelor 2 2%
Student > Doctoral Student 2 2%
Professor 1 1%
Other 4 5%
Unknown 65 78%
Readers by discipline Count As %
Computer Science 7 8%
Biochemistry, Genetics and Molecular Biology 5 6%
Agricultural and Biological Sciences 2 2%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Medicine and Dentistry 1 1%
Other 2 2%
Unknown 65 78%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 June 2011.
All research outputs
#12,846,160
of 22,649,029 outputs
Outputs from BMC Bioinformatics
#3,776
of 7,234 outputs
Outputs of similar age
#129,020
of 155,315 outputs
Outputs of similar age from BMC Bioinformatics
#38
of 45 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,234 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 45th percentile – i.e., 45% 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 155,315 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.