Journal article

Automatic local resolution-based sharpening of cryo-EM maps

Erney Ramirez-Aportela, Jose Luis Vilas, Alisa Glukhova, Roberto Melero, Pablo Conesa, Marta Martinez, David Maluenda, Javier Mota, Amaya Jimenez, Javier Vargas, Roberto Marabini, Patrick M Sexton, Jose Maria Carazo, Carlos Oscar S Sorzano

Bioinformatics | OXFORD UNIV PRESS | Published : 2020

Abstract

MOTIVATION: Recent technological advances and computational developments have allowed the reconstruction of Cryo-Electron Microscopy (cryo-EM) maps at near-atomic resolution. On a typical workflow and once the cryo-EM map has been calculated, a sharpening process is usually performed to enhance map visualization, a step that has proven very important in the key task of structural modeling. However, sharpening approaches, in general, neglects the local quality of the map, which is clearly suboptimal. RESULTS: Here, a new method for local sharpening of cryo-EM density maps is proposed. The algorithm, named LocalDeblur, is based on a local resolution-guided Wiener restoration approach of the or..

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Grants

Awarded by Comunidad de Madrid through grant CAM


Awarded by Spanish Ministry of Economy and Competitiveness


Awarded by Horizon 2020 through grant INSTRUCT-ULTRA (INFRADEV-03-2016-2017)


Awarded by Horizon 2020 through grant iNEXT (INFRAIA-1-2014-2015)


Awarded by European Union through grant INSTRUCT-ULTRA (INFRADEV-03-2016-2017)


Awarded by European Union through grant iNEXT (INFRAIA-1-2014-2015)


Funding Acknowledgements

The authors would like to acknowledge economical support from: the Comunidad de Madrid through grant CAM (S2017/BMD-3817), the Spanish Ministry of Economy and Competitiveness (BIO2016-76400-R) and the European Union and Horizon 2020 through grants INSTRUCT-ULTRA (INFRADEV-03-2016-2017, Proposal: 731005) and iNEXT (INFRAIA-1-2014-2015, Proposal: 653706).