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Functional clustering of time series gene expression data by Granger causality

Overview of attention for article published in BMC Systems Biology, January 2012
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

twitter
2 tweeters

Citations

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16 Dimensions

Readers on

mendeley
48 Mendeley
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4 CiteULike
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Title
Functional clustering of time series gene expression data by Granger causality
Published in
BMC Systems Biology, January 2012
DOI 10.1186/1752-0509-6-137
Pubmed ID
Authors

André Fujita, Patricia Severino, Kaname Kojima, João Sato, Alexandre Patriota, Satoru Miyano

Abstract

A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Cuba 2 4%
Italy 2 4%
Malaysia 1 2%
Austria 1 2%
China 1 2%
Unknown 41 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 29%
Student > Ph. D. Student 9 19%
Student > Master 6 13%
Student > Doctoral Student 3 6%
Professor > Associate Professor 3 6%
Other 9 19%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 10 21%
Engineering 9 19%
Computer Science 9 19%
Biochemistry, Genetics and Molecular Biology 4 8%
Mathematics 3 6%
Other 5 10%
Unknown 8 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 26 July 2020.
All research outputs
#10,376,938
of 17,355,315 outputs
Outputs from BMC Systems Biology
#503
of 1,115 outputs
Outputs of similar age
#86,154
of 161,149 outputs
Outputs of similar age from BMC Systems Biology
#8
of 21 outputs
Altmetric has tracked 17,355,315 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,115 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 49th percentile – i.e., 49% 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 161,149 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 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 52% of its contemporaries.