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Semi-automated quantitative Drosophila wings measurements

Overview of attention for article published in BMC Bioinformatics, June 2017
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Title
Semi-automated quantitative Drosophila wings measurements
Published in
BMC Bioinformatics, June 2017
DOI 10.1186/s12859-017-1720-y
Pubmed ID
Authors

Sheng Yang Michael Loh, Yoshitaka Ogawa, Sara Kawana, Koichiro Tamura, Hwee Kuan Lee

Abstract

Drosophila melanogaster is an important organism used in many fields of biological research such as genetics and developmental biology. Drosophila wings have been widely used to study the genetics of development, morphometrics and evolution. Therefore there is much interest in quantifying wing structures of Drosophila. Advancement in technology has increased the ease in which images of Drosophila can be acquired. However such studies have been limited by the slow and tedious process of acquiring phenotypic data. We have developed a system that automatically detects and measures key points and vein segments on a Drosophila wing. Key points are detected by performing image transformations and template matching on Drosophila wing images while vein segments are detected using an Active Contour algorithm. The accuracy of our key point detection was compared against key point annotations of users. We also performed key point detection using different training data sets of Drosophila wing images. We compared our software with an existing automated image analysis system for Drosophila wings and showed that our system performs better than the state of the art. Vein segments were manually measured and compared against the measurements obtained from our system. Our system was able to detect specific key points and vein segments from Drosophila wing images with high accuracy.

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The data shown below were collected from the profiles of 3 X users 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 26%
Researcher 6 26%
Student > Master 2 9%
Professor 1 4%
Lecturer 1 4%
Other 1 4%
Unknown 6 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 30%
Biochemistry, Genetics and Molecular Biology 4 17%
Chemical Engineering 1 4%
Computer Science 1 4%
Physics and Astronomy 1 4%
Other 2 9%
Unknown 7 30%
Attention Score in Context

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 03 July 2017.
All research outputs
#15,490,321
of 24,549,201 outputs
Outputs from BMC Bioinformatics
#4,891
of 7,552 outputs
Outputs of similar age
#181,582
of 319,819 outputs
Outputs of similar age from BMC Bioinformatics
#62
of 111 outputs
Altmetric has tracked 24,549,201 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,552 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 31st percentile – i.e., 31% 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 319,819 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 111 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.