Abstract：
:Cryo Electron Microscopy is a powerful Structural Biology technique, allowing the elucidation of the three-dimensional structure of biological macromolecules. In particular, the structural study of purified macromolecules -often referred as Single Particle Analysis(SPA)- is normally performed through an iterative process that needs a first estimation of the three-dimensional structure that is progressively refined using experimental data. It is well-known the local optimisation nature of this refinement, so that the initial choice of this first structure may substantially change the final result. Computational algorithms aiming to providing this first structure already exist. However, the question is far from settled and more robust algorithms are still needed so that the refinement process can be performed with sufficient guarantees. In this article we present a new algorithm that addresses the initial volume problem in SPA by setting it in a Weighted Least Squares framework and calculating the weights through a statistical approach based on the cumulative density function of different image similarity measures. We show that the new algorithm is significantly more robust than other state-of-the-art algorithms currently in use in the field. The algorithm is available as part of the software suite Xmipp (http://xmipp.cnb.csic.es) and Scipion (http://scipion.cnb.csic.es) under the name "Significant".
journal_name
J Struct Bioljournal_title
Journal of structural biologyauthors
Sorzano CO,Vargas J,de la Rosa-Trevín JM,Otón J,Álvarez-Cabrera AL,Abrishami V,Sesmero E,Marabini R,Carazo JMdoi
10.1016/j.jsb.2015.01.009subject
Has Abstractpub_date
2015-03-01 00:00:00pages
213-9issue
3eissn
1047-8477issn
1095-8657pii
S1047-8477(15)00025-8journal_volume
189pub_type
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