A framework to refine particle clusters produced by EMAN

Liya Fan; Fa Zhang; Gongming Wang; Zhiyong Liu

doi:10.1093/bioinformatics/btp219

A framework to refine particle clusters produced by EMAN

Liya Fan, Fa Zhang^*, Gongming Wang, Zhiyong Liu

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Motivation: EMAN is one of the most popular software packages for single particle reconstruction. But the particle clusters produced during its model refining stage are of low qualities. We attempt to refine the particle clusters by more accurately determining orientations of particles, and thereby achieving higher resolutions of consequent 3D structures. Results: A particle reclustering framework (PRF) is introduced, which consists of three components. Each of them is responsible for one of the basic tasks of PRF: normalization, threshold determination and reclustering. Our implementation is also described and proved to meet the constraints proposed by PRF. Experiments revealed that our implementation improved resolutions of consequent structures for most cases, but only a little extra execution time was incurred. Therefore, it is practical to incorporate PRF in EMAN to improve qualities of generated 3D structures. Availability and Implementation: Implementation of our algorithm is available upon request from the authors.

Original language	English
Pages (from-to)	i276-i280
Journal	Bioinformatics
Volume	25
Issue number	12
DOIs	https://doi.org/10.1093/bioinformatics/btp219
Publication status	Published - 2009
Externally published	Yes

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abstract = "Motivation: EMAN is one of the most popular software packages for single particle reconstruction. But the particle clusters produced during its model refining stage are of low qualities. We attempt to refine the particle clusters by more accurately determining orientations of particles, and thereby achieving higher resolutions of consequent 3D structures. Results: A particle reclustering framework (PRF) is introduced, which consists of three components. Each of them is responsible for one of the basic tasks of PRF: normalization, threshold determination and reclustering. Our implementation is also described and proved to meet the constraints proposed by PRF. Experiments revealed that our implementation improved resolutions of consequent structures for most cases, but only a little extra execution time was incurred. Therefore, it is practical to incorporate PRF in EMAN to improve qualities of generated 3D structures. Availability and Implementation: Implementation of our algorithm is available upon request from the authors.",

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AB - Motivation: EMAN is one of the most popular software packages for single particle reconstruction. But the particle clusters produced during its model refining stage are of low qualities. We attempt to refine the particle clusters by more accurately determining orientations of particles, and thereby achieving higher resolutions of consequent 3D structures. Results: A particle reclustering framework (PRF) is introduced, which consists of three components. Each of them is responsible for one of the basic tasks of PRF: normalization, threshold determination and reclustering. Our implementation is also described and proved to meet the constraints proposed by PRF. Experiments revealed that our implementation improved resolutions of consequent structures for most cases, but only a little extra execution time was incurred. Therefore, it is practical to incorporate PRF in EMAN to improve qualities of generated 3D structures. Availability and Implementation: Implementation of our algorithm is available upon request from the authors.

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A framework to refine particle clusters produced by EMAN

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