Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead

J. L. Vilas, N. Tabassum, J. Mota, D. Maluenda, A. Jiménez-Moreno, T. Majtner, J. M. Carazo, S. T. Acton, C. O.S. Sorzano

Publikation: Bidrag til tidsskriftReviewForskningpeer review

Resumé

Electron cryomicroscopy (cryoEM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize macromolecular complexes such as ribosomes, viruses, and ion channels. Determination of structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryoEM a scientific rebirth. As a result of these technological advances image processing and analysis have yielded molecular structures at atomic resolution. Nevertheless there continue to be challenges in image processing, and in this article we will touch on the most essential in order to derive an accurate three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. We will then highlight new approaches for each image processing subproblem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking.

OriginalsprogEngelsk
TidsskriftCurrent Opinion in Structural Biology
Vol/bind52
Sider (fra-til)127-145
Antal sider19
ISSN0959-440X
DOI
StatusUdgivet - 1. okt. 2018
Udgivet eksterntJa

Fingeraftryk

Cryoelectron Microscopy
X Ray Crystallography
Cluster Analysis
Viruses
Proteins

Citer dette

Vilas, J. L. ; Tabassum, N. ; Mota, J. ; Maluenda, D. ; Jiménez-Moreno, A. ; Majtner, T. ; Carazo, J. M. ; Acton, S. T. ; Sorzano, C. O.S. / Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead. I: Current Opinion in Structural Biology. 2018 ; Bind 52. s. 127-145.
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abstract = "Electron cryomicroscopy (cryoEM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize macromolecular complexes such as ribosomes, viruses, and ion channels. Determination of structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryoEM a scientific rebirth. As a result of these technological advances image processing and analysis have yielded molecular structures at atomic resolution. Nevertheless there continue to be challenges in image processing, and in this article we will touch on the most essential in order to derive an accurate three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. We will then highlight new approaches for each image processing subproblem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking.",
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Vilas, JL, Tabassum, N, Mota, J, Maluenda, D, Jiménez-Moreno, A, Majtner, T, Carazo, JM, Acton, ST & Sorzano, COS 2018, 'Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead', Current Opinion in Structural Biology, bind 52, s. 127-145. https://doi.org/10.1016/j.sbi.2018.11.004

Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead. / Vilas, J. L.; Tabassum, N.; Mota, J.; Maluenda, D.; Jiménez-Moreno, A.; Majtner, T.; Carazo, J. M.; Acton, S. T.; Sorzano, C. O.S.

I: Current Opinion in Structural Biology, Bind 52, 01.10.2018, s. 127-145.

Publikation: Bidrag til tidsskriftReviewForskningpeer review

TY - JOUR

T1 - Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead

AU - Vilas, J. L.

AU - Tabassum, N.

AU - Mota, J.

AU - Maluenda, D.

AU - Jiménez-Moreno, A.

AU - Majtner, T.

AU - Carazo, J. M.

AU - Acton, S. T.

AU - Sorzano, C. O.S.

PY - 2018/10/1

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N2 - Electron cryomicroscopy (cryoEM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize macromolecular complexes such as ribosomes, viruses, and ion channels. Determination of structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryoEM a scientific rebirth. As a result of these technological advances image processing and analysis have yielded molecular structures at atomic resolution. Nevertheless there continue to be challenges in image processing, and in this article we will touch on the most essential in order to derive an accurate three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. We will then highlight new approaches for each image processing subproblem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking.

AB - Electron cryomicroscopy (cryoEM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize macromolecular complexes such as ribosomes, viruses, and ion channels. Determination of structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryoEM a scientific rebirth. As a result of these technological advances image processing and analysis have yielded molecular structures at atomic resolution. Nevertheless there continue to be challenges in image processing, and in this article we will touch on the most essential in order to derive an accurate three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. We will then highlight new approaches for each image processing subproblem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking.

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