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Image-level and group-level models for Drosophilagene expression pattern annotation

Overview of attention for article published in BMC Bioinformatics, December 2013
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Title
Image-level and group-level models for Drosophilagene expression pattern annotation
Published in
BMC Bioinformatics, December 2013
DOI 10.1186/1471-2105-14-350
Pubmed ID
Authors

Qian Sun, Sherin Muckatira, Lei Yuan, Shuiwang Ji, Stuart Newfeld, Sudhir Kumar, Jieping Ye

Abstract

Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Germany 1 5%
Unknown 20 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 14%
Researcher 3 14%
Student > Postgraduate 3 14%
Professor > Associate Professor 3 14%
Student > Master 1 5%
Other 3 14%
Unknown 6 27%
Readers by discipline Count As %
Computer Science 3 14%
Engineering 3 14%
Agricultural and Biological Sciences 2 9%
Biochemistry, Genetics and Molecular Biology 2 9%
Medicine and Dentistry 2 9%
Other 3 14%
Unknown 7 32%
Attention Score in Context

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 04 December 2013.
All research outputs
#19,015,492
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#6,459
of 7,400 outputs
Outputs of similar age
#235,973
of 310,872 outputs
Outputs of similar age from BMC Bioinformatics
#85
of 105 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
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We're also able to compare this research output to 105 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.