AUTOMATED CRYSTAL QUEUING FOR DATA COLLECTION

用于数据收集的自动水晶排队

• 批准号: 8170005
• 负责人: IRIMPAN I MATHEWS
• 金额: $ 6.1万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170005
• 关键词: Computer Retrieval of Information on Scientific Projects Database; Data; Data Collection; Funding; Grant; Image; Institution; Movement; Process; Productivity; Research; Research Personnel; Resources; Rotation; Running; Sampling; Screening procedure; Source; Testing; Translations; United States National Institutes of Health; beamline; improved; indexing; success

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In order to provide a completely automated process for collecting data from pre-screened crystals, the samples must be repositioned on the goniometer in an automated fashion. In an ideal setup, the users will be able to select good crystals during the screening, assign proper phi values for the data collection, and queue them for the data collection runs. If the users can select all good crystals during screening and set them for data collection, it will improve the beamline efficiency and users productivity. The movements of the crystal in the Hampton tong and other factors of the automated mounting process introduce various amounts of rotation and translation to the crystal between different mountings. Therefore, it is difficult to use the phi values (start and end phi for data collection) selected from the screening process after remounting of the sample. The success of the sample queuing process depends on how accurately the crystal can be repositioned during the second mounting. Repositioning of the sample using the diffraction images and video shots of the sample was explored. The phi shift between two mountings is predicted using the indexing information. Then, sample_x, sample_y, and sample_z translations between the two mountings are calculated by comparing video snapshots at the same phi value. If the space group introduce several equivalent phi values, further analysis of the video images are performed to predict the actual phi shift between the different mountings. Test of this approach indicate that the above analysis provides sufficient information for the queuing of the crystals during the automated screening process, guiding further developemnts.

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 为了提供从预筛选晶体收集数据的完全自动化过程，样品必须以自动化方式重新定位在测角器上。在理想的设置中，用户将能够在筛选期间选择好的晶体，为数据收集分配适当的phi值，并将它们排队用于数据收集运行。如果用户可以在筛选过程中选择所有好的晶体并将其设置为数据收集，将提高束线效率和用户生产力。 晶体在汉普顿钳中的运动和自动安装过程的其它因素在不同安装件之间向晶体引入各种量的旋转和平移。 因此，在重新安装样品后，难以使用从筛选过程中选择的phi值（数据收集的起始和结束phi）。 样品排队过程的成功取决于晶体在第二次安装过程中重新定位的准确程度。 使用样品的衍射图像和视频拍摄的样品的重新定位进行了探索。使用索引信息预测两个安装之间的phi偏移。 然后，通过比较相同phi值下的视频快照来计算两个安装之间的sample_x、sample_y和sample_z平移。 如果空间群引入几个等效的phi值，则执行对视频图像的进一步分析以预测不同安装之间的实际phi偏移。 对该方法的检验表明，上述分析为自动筛选过程中晶体的排队提供了足够的信息，指导了进一步的开发。