| pubmed-article:10331874 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:10331874 | lifeskim:mentions | umls-concept:C0026336 | lld:lifeskim |
| pubmed-article:10331874 | lifeskim:mentions | umls-concept:C0033684 | lld:lifeskim |
| pubmed-article:10331874 | lifeskim:mentions | umls-concept:C0205554 | lld:lifeskim |
| pubmed-article:10331874 | lifeskim:mentions | umls-concept:C0678594 | lld:lifeskim |
| pubmed-article:10331874 | lifeskim:mentions | umls-concept:C1547706 | lld:lifeskim |
| pubmed-article:10331874 | lifeskim:mentions | umls-concept:C0205195 | lld:lifeskim |
| pubmed-article:10331874 | lifeskim:mentions | umls-concept:C1999269 | lld:lifeskim |
| pubmed-article:10331874 | pubmed:issue | 5 | lld:pubmed |
| pubmed-article:10331874 | pubmed:dateCreated | 1999-6-3 | lld:pubmed |
| pubmed-article:10331874 | pubmed:abstractText | In protein crystallography, much time and effort are often required to trace an initial model from an interpretable electron density map and to refine it until it best agrees with the crystallographic data. Here, we present a method to build and refine a protein model automatically and without user intervention, starting from diffraction data extending to resolution higher than 2.3 A and reasonable estimates of crystallographic phases. The method is based on an iterative procedure that describes the electron density map as a set of unconnected atoms and then searches for protein-like patterns. Automatic pattern recognition (model building) combined with refinement, allows a structural model to be obtained reliably within a few CPU hours. We demonstrate the power of the method with examples of a few recently solved structures. | lld:pubmed |
| pubmed-article:10331874 | pubmed:language | eng | lld:pubmed |
| pubmed-article:10331874 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:10331874 | pubmed:citationSubset | IM | lld:pubmed |
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| pubmed-article:10331874 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:10331874 | pubmed:month | May | lld:pubmed |
| pubmed-article:10331874 | pubmed:issn | 1072-8368 | lld:pubmed |
| pubmed-article:10331874 | pubmed:author | pubmed-author:MorrisRR | lld:pubmed |
| pubmed-article:10331874 | pubmed:author | pubmed-author:LamzinV SVS | lld:pubmed |
| pubmed-article:10331874 | pubmed:author | pubmed-author:PerrakisAA | lld:pubmed |
| pubmed-article:10331874 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:10331874 | pubmed:volume | 6 | lld:pubmed |
| pubmed-article:10331874 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:10331874 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:10331874 | pubmed:pagination | 458-63 | lld:pubmed |
| pubmed-article:10331874 | pubmed:dateRevised | 2009-11-19 | lld:pubmed |
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| pubmed-article:10331874 | pubmed:year | 1999 | lld:pubmed |
| pubmed-article:10331874 | pubmed:articleTitle | Automated protein model building combined with iterative structure refinement. | lld:pubmed |
| pubmed-article:10331874 | pubmed:affiliation | European Molecular Biology Laboratory (EMBL), Grenoble Outstation, France. perrakis@embl-grenoble.fr | lld:pubmed |
| pubmed-article:10331874 | pubmed:publicationType | Journal Article | lld:pubmed |
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