.png){kind=icon}
Return
Spatial protein analysis in developing tissues: a sampling-based image processing approach
.png){kind=icon}
OA
AI
DOI：10.1098/rstb.2019.0560.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Advances in fluorescence microscopy approaches have made it relatively easy to generate multi-dimensional image volumes and have highlighted the need for flexible image analysis tools for the extraction of quantitative information from such data. Here we demonstrate that by focusing on simplified feature-based nuclear segmentation and probabilistic cytoplasmic detection we can create a tool that is able to extract geometry-based information from diverse mammalian tissue images. Our open-source image analysis platform, called 'SilentMark', can cope with three-dimensional noisy images and with crowded fields of cells to quantify signal intensity in different cellular compartments. Additionally, it provides tissue geometry related information, which allows one to quantify protein distribution with respect to marked regions of interest. The lightweight SilentMark algorithms have the advantage of not requiring multiple processors, graphics cards or training datasets and can be run even with just several hundred megabytes of memory. This makes it possible to use the method as a Web application, effectively eliminating setup hurdles and compatibility issues with operating systems. We test this platform on mouse pre-implantation embryos, embryonic stem cell-derived embryoid bodies and mouse embryonic heart, and relate protein localization to tissue geometry. This article is part of a discussion meeting issue 'Contemporary morphogenesis'.
Keywords:
image analysis
immunofluorescence
protein quantification
segmentation
gene expression
cell and developmental biology
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.7
Papers:
8.7K
Citations:
5.6W
Organization
Cited Papers
ShareSaveThe Hippo Signaling Pathway Components Lats and Yap Pattern Tead4 Activity to Distinguish Mouse Trophectoderm from Inner Cell Mass.png)
DEVELOPMENTAL CELL
OAAI
DEVELOPMENTAL CELLIF8.7
OAAIShareSaveShareSaveReal-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing EmbryosDEVELOPMENTAL CELLOAAI
DEVELOPMENTAL CELLIF8.7
OAAIShareSaveImaging plant growth in 4D: robust tissue reconstruction and lineaging at cell resolutionNATURE METHODS
NATURE METHODSIF32.1
PREAI
ShareSaveA Concise Catalytic Route to the Marine Sesquiterpenoids (–)‐Clavukerin A and (–)‐Isoclavukerin A
PREAI
ShareSaveThe Cardiac Transcription Network Modulated by Gata4, Mef2a, Nkx2.5, Srf, Histone Modifications, and MicroRNAsPLOS GENETICSOAAI
PLOS GENETICSIF3.7
OAAIShareSave
View more