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首页> 外文期刊>Acta crystallographica.Section D. Biological crystallography >The application of hierarchical cluster analysis to the selection of isomorphous crystals
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The application of hierarchical cluster analysis to the selection of isomorphous crystals

机译:层序聚类分析的应用同晶型晶体的选择

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It is generally assumed that the quality of X-ray diffraction data can be improved by merging data sets from several crystals. However, this effect is only valid if the data sets used are from crystals that are structurally identical. It is found that frozen macromolecular crystals very often have relatively low structure identity (and are therefore not isomorphous); thus, to obtain a real gain from multi-crystal data sets one needs to make an appropriate selection of structurally similar crystals. The application of hierarchical cluster analysis, based on the matrix of the correlation coefficient between scaled intensities, is proposed for the identification of isomorphous data sets. Multi-crystal single-wavelength anomalous dispersion data sets from four different protein molecules have been probed to test the applicability of this method. The use of hierarchical cluster analysis permitted the selection of batches of data sets which when merged together significantly improved the crystallographic indicators of the merged data and allowed solution of the structure.
机译:一般认为,x射线的质量衍射数据可以提高通过合并数据集从几个晶体。只所使用的数据集是否有效晶体结构是相同的。发现冷冻大分子晶体非常经常有身份(和相对较低的结构因此没有同形);真正的获得多晶数据集一个需求一个适当的选择结构类似的晶体。聚类分析,基于矩阵的相关系数之间的比例强度,提出了识别同形的数据集。单波长反常色散数据集从四个不同的蛋白质分子探索测试该方法的适用性。层序聚类分析的使用允许选择批次的数据集当合并在一起大大改善了合并后的晶体指标数据和允许结构的解决方案。

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