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Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning
Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the assessment of structural heterogeneity. However, traditional algorithms for uns...
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| Publicado no: | PLoS One |
|---|---|
| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5546606/ https://ncbi.nlm.nih.gov/pubmed/28786986 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0182130 |
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