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Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks
Visualization algorithms are fundamental tools for interpreting single-cell data. However, standard methods, such as t-stochastic neighbor embedding (t-SNE), are not scalable to datasets with millions of cells and the resulting visualizations cannot be generalized to analyze new datasets. Here we in...
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| Publicado no: | Cell Syst |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6469860/ https://ncbi.nlm.nih.gov/pubmed/29936184 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.cels.2018.05.017 |
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