Learning representations for image-based profiling of perturbations
Abstract Measuring the phenotypic effect of treatments on cells through imaging assays is an efficient and powerful way of studying cell biology, and requires computational methods for transforming images into quantitative data. Here, we present an improved strategy for learning representations of t...
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| Principais autores: | , , , , , , , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2024-02-01
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| coleção: | Nature Communications |
| Acesso em linha: | https://doi.org/10.1038/s41467-024-45999-1 |
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