Abstract:
:In cryo-electron microscopy (cryo-EM) single-particle reconstruction, the heterogeneity of two-dimensional projection image data resulting from the co-existence of different conformational or ligand binding states of a macromolecular complex remains a major obstacle as it impairs the validity of reconstructed density maps and limits the progress toward higher resolution. Classification of cryo-EM data according to the different conformations is difficult because of the coexistence of multiple orientations in a single dataset. Here, we present an unsupervised classification method, termed cluster tracking, which utilizes the continuity in multi-dimensional space induced by angular adjacency of projections in large datasets. In a proof of concept, the testing of cluster tracking on simulated projection data, which were generated from multiple conformations and orientations of an existing volume, produced clusters that are consistent with the conformational identity of the data. The application of the method to experimental cryo-EM projection data is found to result in a partition similar to the one generated by supervised classification.
journal_name
J Struct Bioljournal_title
Journal of structural biologyauthors
Fu J,Gao H,Frank Jdoi
10.1016/j.jsb.2006.06.012subject
Has Abstractpub_date
2007-01-01 00:00:00pages
226-39issue
1eissn
1047-8477issn
1095-8657pii
S1047-8477(06)00200-0journal_volume
157pub_type
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