Methods In Mass Spectrometry

用于分析蛋白质结构的质谱学方法正在得到改进，并在蛋白质组学的独立和合作研究项目中得到应用和测试。分离方法和数据处理方面的项目正在进行中。在过去的一年里，在以下方面取得了进展：为处理蛋白质组学数据建立了一个计算环境；将同位素标记的融合蛋白作为蛋白质标准；对多套复杂的液相色谱-高分辨率质谱学数据中已识别和未识别的成分进行了量化；以及关于蛋白质组学标准的多机构合作研究。 处理和挖掘质谱学蛋白质组数据需要一个系统，使调查人员能够使用台式计算机访问兆兆字节的数据；能够使用新兴的软件工具反复探测他们的数据；以及能够将这些数据转移到公共档案储存库。一个通用的系统已经在LNT中实现，并将与NIH的其他蛋白质组学小组共享。

Mass spectrometric methods for the analysis of protein structures are being improved, applied and tested in independent and collaborative research projects in proteomics. Projects in separation methods and data processing are in progress. In the past year, progress has been made on implementation of a computational environment for mass spectrometric proteomic data processing; isotope labeled fusion proteins as protein standards; quantification of identified and unidentified components in sets of complex liquid chromatography-high resolution mass spectrometry data; and multi-institutional collaborative studies on standards in proteomics. The processing and mining of mass spectrometric proteomic data requires a system allowing investigators desktop computer access to terabytes of data; the ability to repeatedly probe their data with emerging software tools; and the ability to transfer this data to public archival repositories. A versatile system has been implemented in LNT and will be shared with other proteomics groups in NIH.