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Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps
Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982917/ https://www.ncbi.nlm.nih.gov/pubmed/31878333 http://dx.doi.org/10.3390/molecules25010082 |
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author | Alnabati, Eman Kihara, Daisuke |
author_facet | Alnabati, Eman Kihara, Daisuke |
author_sort | Alnabati, Eman |
collection | PubMed |
description | Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting, flexible fitting, and de novo modeling methods. It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. Here, we review these different categories of macromolecule structure modeling methods and discuss their advances over time. |
format | Online Article Text |
id | pubmed-6982917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-69829172020-02-06 Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps Alnabati, Eman Kihara, Daisuke Molecules Review Cryo-electron microscopy (cryo-EM) has now become a widely used technique for structure determination of macromolecular complexes. For modeling molecular structures from density maps of different resolutions, many algorithms have been developed. These algorithms can be categorized into rigid fitting, flexible fitting, and de novo modeling methods. It is also observed that machine learning (ML) techniques have been increasingly applied following the rapid progress of the ML field. Here, we review these different categories of macromolecule structure modeling methods and discuss their advances over time. MDPI 2019-12-24 /pmc/articles/PMC6982917/ /pubmed/31878333 http://dx.doi.org/10.3390/molecules25010082 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Alnabati, Eman Kihara, Daisuke Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps |
title | Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps |
title_full | Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps |
title_fullStr | Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps |
title_full_unstemmed | Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps |
title_short | Advances in Structure Modeling Methods for Cryo-Electron Microscopy Maps |
title_sort | advances in structure modeling methods for cryo-electron microscopy maps |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982917/ https://www.ncbi.nlm.nih.gov/pubmed/31878333 http://dx.doi.org/10.3390/molecules25010082 |
work_keys_str_mv | AT alnabatieman advancesinstructuremodelingmethodsforcryoelectronmicroscopymaps AT kiharadaisuke advancesinstructuremodelingmethodsforcryoelectronmicroscopymaps |