Automated image analysis reduces user to user variability in flow cytometry gating strategies
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- Опубліковано 1 жов 2024
- Presented By: Erin Taylor
Speaker Biography: Erin’s career started in public health and human services, working with multiple vulnerable and medically underserved populations in both healthcare and research settings...
Webinar: Automated image analysis reduces user to user variability in flow cytometry gating strategies
Webinar Abstract: Differences in how users gate populations within experiments are major sources of variability in flow cytometry data analysis. Incorporating automated image analysis can substantially reduce user bias. Users are given access to an expansive array of image-derived label-free parameters that can help with assessment of sample quality, optimization of gating strategies, and discovery of morphological features that are not resolved with light scatter or fluorescence parameters...
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