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Acta Crystallographica Section D Structural Biology
Article . 2018 . Peer-reviewed
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PubMed Central
Article . 2018
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https://doi.org/10.1101/247049...
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Automated map sharpening by maximization of detail and connectivity

Authors: Thomas C. Terwilliger; Oleg V. Sobolev; Pavel V. Afonine; Paul D. Adams;

Automated map sharpening by maximization of detail and connectivity

Abstract

Synopsis A procedure for optimizing the sharpening of a map based on maximizing the level of detail and connectivity of the map is developed and applied to 361 pairs of deposited cryo-EM maps and associated models. Abstract We present an algorithm for automatic map sharpening that is based on optimization of detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures in a metric we term “adjusted surface area”, we can evaluate map quality in an automated fashion. We use this metric to choose optimal map sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally-sharpened map. To evaluate the performance of various approaches, we use a simple metric based on map-model correlation that can reproduce visual choices of optimally-sharpened maps. The map-model correlation is calculated using a model with B-factors (atomic displacement factors, ADP) set to zero. We use this model-based metric to evaluate map sharpening, use it to evaluate map sharpening approaches and find that optimization of adjusted surface area can be an effective tool for map sharpening.

Country
United States
Keywords

Models, Molecular, map sharpening, Bacterial Toxins, TRPV Cation Channels, cryo-electron microscopy, Crystallography, X-Ray, Connexins, Bacterial Proteins, Models, Animals, Humans, Antigens, X-ray crystallography, Antigens, Bacterial, Crystallography, Fourier Analysis, map interpretation, Cryoelectron Microscopy, Bacterial, Molecular, Biological Sciences, Research Papers, 620, Chemical Sciences, Physical Sciences, X-Ray, Algorithms

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    227
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
227
Top 1%
Top 1%
Top 0.1%
Green
hybrid