ArticleMethods in molecular biology (Clifton, N.J.)2013
A high content imaging-based approach for classifying cellular phenotypes.
Article in Methods in molecular biology (Clifton, N.J.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- In-process evaluation of culture errors using morphology-based image analysis.Regenerative therapy · 2018Article
- Organizational metrics of interchromatin speckle factor domains: integrative classifier for stem cell adhesion & lineage signaling.Integrative biology : quantitative biosciences from nano to macro · 2015Article
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Authors and funding
3 authors.
Funding
Abstract
Current methods to characterize cell-biomaterial interactions are population-based and rely on imaging or biochemical analysis of end-point biological markers. The analysis of stem cells in cultures is further challenged by the heterogeneous nature and divergent fates of stem cells, especially in complex, engineered microenvironments. Here, we describe a high content imaging-based platform capable of identifying cell subpopulations based on cell phenotype-specific morphological descriptors. This method can be utilized to identify microenvironment-responsive morphological descriptors, which can be used to parse cells from a heterogeneous cell population based on emergent phenotypes at the single-cell level and has been successfully deployed to forecast long-term cell lineage fates and screen regenerative phenotype-prescriptive biomaterials.
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Registered trials
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