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- Refinement and Optimization based on Machine lEarning for cryo-EM
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- Youdong Mao <>
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(Wu et al., 2017)
Massively parallel unsupervised single-particle cryo-EM data clustering via statistical manifold learning.
PMID: 28786986 DOI: 10.1371/journal.pone.0182130
A Bayesian view on cryo-EM structure determination.
J Mol Biol.
PMID: 22100448 DOI: 10.1016/j.jmb.2011.11.010
A maximum-likelihood approach to single-particle image refinement.
J Struct Biol.
PMID: 9774537 DOI: 10.1006/jsbi.1998.4014
State Key Laboratory for Artificial Microstructure and Mesoscopic Physics, Institute of Condensed Matter Physics, School of Physics, Center for Quantitative Biology, Peking University, Beijing, China; Intel Parallel Computing Center for Structural Biology, Dana-Farber Cancer Institute, Boston, MA, USA; Software and Services Group, Intel Corporation, Santa Clara, CA, USA; Department of Biophysics, Peking University Health Science Center, Beijing, China; Peking Tsinghua Joint Center for Life Sciences, Peking University, Beijing, China; Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA, USA
Supported by a grant of the Thousand Talents Plan of China, by a grant from National Natural Science Foundation of China (Grant No. 91530321), and by an Intel Corporation academic grant.
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