| Title |
An automated image analysis method to measure regularity in biological patterns: a case study in a Drosophila neurodegenerative model
|
|---|---|
| Published in |
Molecular Neurodegeneration, March 2015
|
| DOI | 10.1186/s13024-015-0005-z |
| Pubmed ID | |
| Authors |
Sergio Diez-Hermano, Jorge Valero, Cristina Rueda, Maria D Ganfornina, Diego Sanchez |
| Abstract |
The fruitfly compound eye has been broadly used as a model for neurodegenerative diseases. Classical quantitative techniques to estimate the degeneration level of an eye under certain experimental conditions rely either on time consuming histological techniques to measure retinal thickness, or pseudopupil visualization and manual counting. Alternatively, visual examination of the eye surface appearance gives only a qualitative approximation provided the observer is well-trained. Therefore, there is a need for a simplified and standardized analysis of fruitfly eye degeneration extent for both routine laboratory use and for automated high-throughput analysis. We have designed the freely available ImageJ plugin FLEYE, a novel and user-friendly method for quantitative unbiased evaluation of neurodegeneration levels based on the acquisition of fly eye surface pictures. The incorporation of automated image analysis tools and a classification algorithm sustained on a built-in statistical model allow the user to quickly analyze large sample size data with reliability and robustness. Pharmacological screenings or genetic studies using the Drosophila retina as a model system may benefit from our method, because it can be easily implemented in a fully automated environment. In addition, FLEYE can be trained to optimize the image detection capabilities, resulting in a versatile approach to evaluate the pattern regularity of other biological or non-biological samples and their experimental or pathological disruption. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| China | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Netherlands | 1 | 2% |
| Turkey | 1 | 2% |
| Unknown | 42 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 22% |
| Researcher | 8 | 18% |
| Student > Ph. D. Student | 6 | 13% |
| Student > Bachelor | 5 | 11% |
| Student > Doctoral Student | 4 | 9% |
| Other | 7 | 16% |
| Unknown | 5 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 33% |
| Biochemistry, Genetics and Molecular Biology | 10 | 22% |
| Neuroscience | 5 | 11% |
| Engineering | 3 | 7% |
| Nursing and Health Professions | 1 | 2% |
| Other | 5 | 11% |
| Unknown | 6 | 13% |
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 12 April 2022.
All research outputs
#14,431,072
of 23,577,654 outputs
Outputs from Molecular Neurodegeneration
#696
of 875 outputs
Outputs of similar age
#133,458
of 260,376 outputs
Outputs of similar age from Molecular Neurodegeneration
#15
of 15 outputs
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