https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2022Vilas_Emerging2022Vilas Emerging - Revision history2026-05-13T09:47:59ZRevision history for this page on the wikiMediaWiki 1.44.2https://3demmethods.i2pc.es/index.php?title=2022Vilas_Emerging&diff=5173&oldid=prevWikiSysop: Created page with "== Citation == Vilas, J.L., Carazo, J.M. and Sorzano, C.O.S. 2022. Emerging themes in CryoEM─ Single particle analysis image processing. Chemical Reviews. 122, 17 (2022), 13915–13951. == Abstract == Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars hav..."2026-03-24T10:44:34Z<p>Created page with "== Citation == Vilas, J.L., Carazo, J.M. and Sorzano, C.O.S. 2022. Emerging themes in CryoEM─ Single particle analysis image processing. Chemical Reviews. 122, 17 (2022), 13915–13951. == Abstract == Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars hav..."</p>
<p><b>New page</b></p><div>== Citation ==<br />
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Vilas, J.L., Carazo, J.M. and Sorzano, C.O.S. 2022. Emerging themes in CryoEM─ Single particle analysis image processing. Chemical Reviews. 122, 17 (2022), 13915–13951.<br />
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== Abstract ==<br />
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Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.<br />
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== Keywords ==<br />
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== Links ==<br />
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https://pubs.acs.org/doi/10.1021/acs.chemrev.1c00850<br />
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== Comments ==</div>WikiSysop