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Integrating fMRI and SNP data for biomarker identification for schizophrenia with a sparse representation based variable selection method.

Overview of attention for article published in BMC Medical Genomics, November 2013
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 tweeter

Citations

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19 Dimensions

Readers on

mendeley
47 Mendeley
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Title
Integrating fMRI and SNP data for biomarker identification for schizophrenia with a sparse representation based variable selection method.
Published in
BMC Medical Genomics, November 2013
DOI 10.1186/1755-8794-6-s3-s2
Pubmed ID
Authors

Cao H, Duan J, Lin D, Calhoun V, Wang YP

Abstract

In recent years, both single-nucleotide polymorphism (SNP) array and functional magnetic resonance imaging (fMRI) have been widely used for the study of schizophrenia (SCZ). In addition, a few studies have been reported integrating both SNPs data and fMRI data for comprehensive analysis.

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

Geographical breakdown

Country Count As %
United States 3 6%
Spain 1 2%
Unknown 43 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 21%
Researcher 8 17%
Professor > Associate Professor 6 13%
Student > Postgraduate 4 9%
Student > Master 4 9%
Other 7 15%
Unknown 8 17%
Readers by discipline Count As %
Medicine and Dentistry 9 19%
Biochemistry, Genetics and Molecular Biology 6 13%
Engineering 6 13%
Agricultural and Biological Sciences 5 11%
Neuroscience 5 11%
Other 5 11%
Unknown 11 23%

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 21 October 2014.
All research outputs
#2,295,820
of 4,507,652 outputs
Outputs from BMC Medical Genomics
#178
of 310 outputs
Outputs of similar age
#61,612
of 124,492 outputs
Outputs of similar age from BMC Medical Genomics
#7
of 13 outputs
Altmetric has tracked 4,507,652 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 310 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 29th percentile – i.e., 29% 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 124,492 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.