Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections...

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Detalles Bibliográficos
Autores principales: Xu, Yaofang, Wu, Jiayi, Yin, Chang-Cheng, Mao, Youdong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154524/
https://www.ncbi.nlm.nih.gov/pubmed/27959895
http://dx.doi.org/10.1371/journal.pone.0167765

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5154524/
https://www.ncbi.nlm.nih.gov/pubmed/27959895
http://dx.doi.org/10.1371/journal.pone.0167765

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