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Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison

Overview of attention for article published in BMC Systems Biology, January 2012
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Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
58 Mendeley
citeulike
2 CiteULike
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Title
Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison
Published in
BMC Systems Biology, January 2012
DOI 10.1186/1752-0509-6-53
Pubmed ID
Authors

Michalis K Titsias, Antti Honkela, Neil D Lawrence, Magnus Rattray

Abstract

Complete transcriptional regulatory network inference is a huge challenge because of the complexity of the network and sparsity of available data. One approach to make it more manageable is to focus on the inference of context-specific networks involving a few interacting transcription factors (TFs) and all of their target genes.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Spain 1 2%
Sweden 1 2%
Brazil 1 2%
Unknown 52 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 45%
Student > Ph. D. Student 12 21%
Professor > Associate Professor 5 9%
Professor 4 7%
Student > Master 4 7%
Other 6 10%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 41%
Computer Science 11 19%
Biochemistry, Genetics and Molecular Biology 8 14%
Mathematics 6 10%
Engineering 2 3%
Other 4 7%
Unknown 3 5%

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 15 April 2022.
All research outputs
#12,880,448
of 22,716,996 outputs
Outputs from BMC Systems Biology
#432
of 1,142 outputs
Outputs of similar age
#143,016
of 244,177 outputs
Outputs of similar age from BMC Systems Biology
#26
of 46 outputs
Altmetric has tracked 22,716,996 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 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 60% 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 244,177 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.