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Theoretical and practical approaches to improve the performance of local correlation algorithms for volume data analysis and shape recognition
Author(s) -
Titarenko Valeriy,
Roseman Alan M.
Publication year - 2021
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.374
H-Index - 138
ISSN - 2059-7983
DOI - 10.1107/s2059798321001212
Subject(s) - similarity (geometry) , translation (biology) , algorithm , rotation (mathematics) , computer science , volume (thermodynamics) , reduction (mathematics) , fourier transform , discrete fourier transform (general) , correlation , artificial intelligence , mathematics , fourier analysis , image (mathematics) , short time fourier transform , geometry , physics , mathematical analysis , biochemistry , chemistry , quantum mechanics , messenger rna , gene
In this paper, several approaches to be used to accelerate algorithms for fitting an atomic structure into a given 3D density map determined by cryo‐EM are discussed. Rotation and translation of the atomic structure to find similarity scores are used and implemented with discrete Fourier transforms. Several rotations can be combined into groups to accelerate processing. The finite resolution of experimental and simulated maps allows a reduction in the number of rotations and translations needed in order to estimate similarity‐score values.