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Predicting single-cell gene expression profiles of imaging flow cytometry data with machine learning
High-content imaging and single-cell genomics are two of the most prominent high-throughput technologies for studying cellular properties and functions at scale. Recent studies have demonstrated that information in large imaging datasets can be used to estimate gene mutations and to predict the cell...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672460/ https://www.ncbi.nlm.nih.gov/pubmed/33119742 http://dx.doi.org/10.1093/nar/gkaa926 |