pomBseen: An automated pipeline for analysis of fission yeast images.
Makoto OhiraNicholas RhindPublished in: PloS one (2023)
Fission yeast is a model organism widely used for studies of eukaryotic cell biology. As such, it is subject to bright-field and fluorescent microscopy. Manual analysis of such data can be laborious and subjective. Therefore, we have developed pomBseen, an image analysis pipeline for the quantitation of fission yeast micrographs containing a bright-field channel and up to two fluorescent channels. It accepts a wide range of image formats and produces a table with the size and total and nuclear fluorescent intensities of the cells in the image. Benchmarking of the pipeline against manually annotated datasets demonstrates that it reliably segments cells and acquires their image parameters. Written in MATLAB, pomBseen is also available as a standalone application.
Keyphrases
- deep learning
- induced apoptosis
- quantum dots
- cell cycle arrest
- living cells
- label free
- ms ms
- single cell
- high resolution
- endoplasmic reticulum stress
- stem cells
- convolutional neural network
- optical coherence tomography
- high throughput
- single molecule
- cell death
- oxidative stress
- mesenchymal stem cells
- cell wall
- artificial intelligence
- rna seq
- pi k akt
- fluorescent probe