Cargando…
FEM: feature-enhanced map
A method is presented that modifies a 2m F (obs) − D F (model) σ(A)-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple meth...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4356370/ https://www.ncbi.nlm.nih.gov/pubmed/25760612 http://dx.doi.org/10.1107/S1399004714028132 |
Sumario: | A method is presented that modifies a 2m F (obs) − D F (model) σ(A)-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2m F (obs) − D F (model) σ(A)-weighted map. |
---|