期刊
BIOMEDICINES
卷 9, 期 9, 页码 -出版社
MDPI
DOI: 10.3390/biomedicines9091222
关键词
retinogenesis; quantitative biology; imaging
资金
- Spanish Ministerio de Econoima y Competitividad [BFU2014-53299-P, RTI2018-096953-B-I00]
- IFIMAC-UAM, through the 'Maria de Maeztu' Programme for Units of Excellence in R&D from the Spanish Ministerio de Economia y Competitividad [CEX2018-000805-M]
- Fundacion Ramon Areces and Banco de Santander
The study of vertebrate retina development can be approached from various perspectives, ranging from qualitative to quantitative, and focuses on spatial-temporal features, three-dimensional structure, and regulation at the systems level. Using the example of the developing zebrafish retina, the importance of image quality, processing, and algorithms in extracting quantitative data from dense three-dimensional tissues is highlighted. It is suggested that the scientific community focusing on developmental systems could greatly benefit from a detailed disclosure of tools and pipelines used for processing and analyzing images from biological samples.
The study of the development of the vertebrate retina can be addressed from several perspectives: from a purely qualitative to a more quantitative approach that takes into account its spatio-temporal features, its three-dimensional structure and also the regulation and properties at the systems level. Here, we review the ongoing transition toward a full four-dimensional characterization of the developing vertebrate retina, focusing on the challenges at the experimental, image acquisition, image processing and quantification. Using the developing zebrafish retina, we illustrate how quantitative data extracted from these type of highly dense, three-dimensional tissues depend strongly on the image quality, image processing and algorithms used to segment and quantify. Therefore, we propose that the scientific community that focuses on developmental systems could strongly benefit from a more detailed disclosure of the tools and pipelines used to process and analyze images from biological samples.
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