So far fluorescent stains have been used to assign cells to their cell cycle phase. These chemicals damage the cells and may distort the results. Scientists of the Helmholtz Zentrum München in collaboration with the Broad Institute of MIT and Harvard, Swansea University, Newcastle University and The Francis Crick Institute have now found an alternative.
"We used two generally neglected data sources: the bright and the darkfield images" says Thomas Blasi, PhD student at the ICB and first author of the publication. "We could use the information in these data for machine learning." This approach makes it possible to not only classify cells, but also to digitally sort them with a high level of specificity. Based on these findings the Broad Institute and the Helmholtz Zentrum München also filed a provisional patent application.
"Computer-based classification of cells based on large population of cell images opens up new perspectives. This approach could also be used in many different contexts, not only for cell cycle analysis," adds Prof. Dr. Dr. Fabian Theis, head of the ICB.
The above post is reprinted from materials provided by Helmholtz Zentrum München - German Research Center for Environmental Health. Note: Materials may be edited for content and length.
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