FEM: feature-enhanced map

By Pavel V. Afonine, Nigel W. Moriarty, M. Mustyakimov, O. Sobolev, T. C. Terwilliger, D. Turk, Alexandre Urzhumtsev, Paul D. Adams. 2014

165 citations recorded by the source corpus.

The non-iterative feature-enhancing approach improves crystallographic maps’ interpretability by reducing model bias and noise and strengthening the existing signal.

Subfields: Electronic, Optical and Magnetic Materials, Mechanical Engineering, Mechanics of Materials

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In Electronic, Optical and Magnetic Materials

1. Pavel V. Afonine
2. Alexandre Urzhumtsev
3. Paul D. Adams

Citations in the corpus

• Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix (2019, background): “(iii) Feature-enhanced maps (FEM; phenix.feature_ enhanced_map) modify a 2mFobs DFmodel A-weighted map so that weak signals are strengthened while model bias and noise are reduced (Afonine et al., 2015).”
• Automated map sharpening by maximization of detail and connectivity (2018, methodology): “For example, the Phenix feature-enhanced maps (FEM, Afonine et al., 2015) and the model-building software Coot (Emsley et al., 2010) use maximization of the kurtosis of a map to choose an overall sharpening Bsharpen (an exponential factor applied to Fourier terms, cf. DeLaBarre and Brunger, 2006;…”
• Current approaches for the fitting and refinement of atomic models into cryo-EM maps using CCP-EM (2018, methodology): “…in features in the map being revealed (Brunger et al., 2009; Nicholls et al., 2012), noting that other approaches towards map modification have been employed with a similar objective both in the context of MX (Afonine et al., 2015) and cryo-EM (Jakobi et al., 2017; Terwilliger et al., 2018).”