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Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks
A fundamental problem in biomedical research is the low number of observations available, mostly due to a lack of available biosamples, prohibitive costs, or ethical reasons. Augmenting few real observations with generated in silico samples could lead to more robust analysis results and a higher rep...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952370/ https://www.ncbi.nlm.nih.gov/pubmed/31919373 http://dx.doi.org/10.1038/s41467-019-14018-z |