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Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers
Modeling bifurcations in single-cell transcriptomics data has become an increasingly popular field of research. Several methods have been proposed to infer bifurcation structure from such data, but all rely on heuristic non-probabilistic inference. Here we propose the first generative, fully probabi...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
F1000Research
2017
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428745/ https://www.ncbi.nlm.nih.gov/pubmed/28503665 http://dx.doi.org/10.12688/wellcomeopenres.11087.1 |