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Generative modeling of single-cell gene expression for dose-dependent chemical perturbations
Single-cell sequencing reveals the heterogeneity of cellular response to chemical perturbations. However, testing all relevant combinations of cell types, chemicals, and doses is a daunting task. A deep generative learning formalism called variational autoencoders (VAEs) has been effective in predic...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10436058/ https://www.ncbi.nlm.nih.gov/pubmed/37602218 http://dx.doi.org/10.1016/j.patter.2023.100817 |