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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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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

policy
1 policy source
twitter
2 tweeters

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
51 Mendeley
citeulike
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 51 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 44 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 27%
Student > Ph. D. Student 11 22%
Student > Master 7 14%
Professor 3 6%
Student > Doctoral Student 3 6%
Other 9 18%
Unknown 4 8%
Readers by discipline Count As %
Computer Science 11 22%
Agricultural and Biological Sciences 10 20%
Engineering 9 18%
Biochemistry, Genetics and Molecular Biology 3 6%
Mathematics 3 6%
Other 7 14%
Unknown 8 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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
#5,953,362
of 21,339,655 outputs
Outputs from BMC Systems Biology
#232
of 1,138 outputs
Outputs of similar age
#46,894
of 177,147 outputs
Outputs of similar age from BMC Systems Biology
#16
of 68 outputs
Altmetric has tracked 21,339,655 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,138 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 78% of its peers.
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 177,147 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.