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iCTNet: A Cytoscape plugin to produce and analyze integrative complex traits networks

Overview of attention for article published in BMC Bioinformatics, September 2011
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Mentioned by

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1 X user

Citations

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34 Dimensions

Readers on

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89 Mendeley
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6 CiteULike
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Title
iCTNet: A Cytoscape plugin to produce and analyze integrative complex traits networks
Published in
BMC Bioinformatics, September 2011
DOI 10.1186/1471-2105-12-380
Pubmed ID
Authors

Lili Wang, Pouya Khankhanian, Sergio E Baranzini, Parvin Mousavi

Abstract

The speed at which biological datasets are being accumulated stands in contrast to our ability to integrate them meaningfully. Large-scale biological databases containing datasets of genes, proteins, cells, organs, and diseases are being created but they are not connected. Integration of these vast but heterogeneous sources of information will allow the systematic and comprehensive analysis of molecular and clinical datasets, spanning hundreds of dimensions and thousands of individuals. This integration is essential to capitalize on the value of current and future molecular- and cellular-level data on humans to gain novel insights about health and disease.

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

Geographical breakdown

Country Count As %
Germany 6 7%
United Kingdom 2 2%
Spain 2 2%
France 1 1%
Portugal 1 1%
United States 1 1%
Unknown 76 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 26%
Researcher 19 21%
Professor > Associate Professor 8 9%
Student > Postgraduate 6 7%
Other 5 6%
Other 17 19%
Unknown 11 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 35%
Biochemistry, Genetics and Molecular Biology 14 16%
Medicine and Dentistry 12 13%
Computer Science 6 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 3%
Other 10 11%
Unknown 13 15%
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 05 October 2011.
All research outputs
#18,297,449
of 22,653,392 outputs
Outputs from BMC Bioinformatics
#6,276
of 7,236 outputs
Outputs of similar age
#109,237
of 131,235 outputs
Outputs of similar age from BMC Bioinformatics
#78
of 84 outputs
Altmetric has tracked 22,653,392 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 7,236 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 131,235 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 84 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.