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Ensemble learning for classifying single-cell data and projection across reference atlases
SUMMARY: Single-cell data are being generated at an accelerating pace. How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell typ...
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| Publicado no: | Bioinformatics |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7267838/ https://ncbi.nlm.nih.gov/pubmed/32105316 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa137 |
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