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Putative synaptic genes defined from a Drosophila whole body developmental transcriptome by a machine learning approach

Overview of attention for article published in BMC Genomics, September 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)

Mentioned by

twitter
4 tweeters
patent
3 patents

Citations

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15 Dimensions

Readers on

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43 Mendeley
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Title
Putative synaptic genes defined from a Drosophila whole body developmental transcriptome by a machine learning approach
Published in
BMC Genomics, September 2015
DOI 10.1186/s12864-015-1888-3
Pubmed ID
Authors

Flavio Pazos Obregón, Cecilia Papalardo, Sebastián Castro, Gustavo Guerberoff, Rafael Cantera

Abstract

Assembly and function of neuronal synapses require the coordinated expression of a yet undetermined set of genes. Although roughly a thousand genes are expected to be important for this function in Drosophila melanogaster, just a few hundreds of them are known so far. In this work we trained three learning algorithms to predict a "synaptic function" for genes of Drosophila using data from a whole-body developmental transcriptome published by others. Using statistical and biological criteria to analyze and combine the predictions, we obtained a gene catalogue that is highly enriched in genes of relevance for Drosophila synapse assembly and function but still not recognized as such. The utility of our approach is that it reduces the number of genes to be tested through hypothesis-driven experimentation.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Netherlands 1 2%
Uruguay 1 2%
Unknown 40 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 44%
Researcher 5 12%
Student > Bachelor 4 9%
Student > Doctoral Student 2 5%
Student > Master 2 5%
Other 1 2%
Unknown 10 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 30%
Biochemistry, Genetics and Molecular Biology 10 23%
Neuroscience 6 14%
Medicine and Dentistry 2 5%
Computer Science 1 2%
Other 1 2%
Unknown 10 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 23 August 2022.
All research outputs
#4,529,556
of 22,514,578 outputs
Outputs from BMC Genomics
#1,918
of 10,558 outputs
Outputs of similar age
#57,237
of 258,125 outputs
Outputs of similar age from BMC Genomics
#1
of 1 outputs
Altmetric has tracked 22,514,578 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,558 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 81% 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 258,125 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them