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Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions
Existing computational methods that use single-cell RNA-sequencing (scRNA-seq) for cell fate prediction do not model how cells evolve stochastically and in physical time, nor can they predict how differentiation trajectories are altered by proposed interventions. We introduce PRESCIENT (Potential en...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163769/ https://www.ncbi.nlm.nih.gov/pubmed/34050150 http://dx.doi.org/10.1038/s41467-021-23518-w |