Department of Chemistry, Brown University, Providence, RI 02903, USA.
Proteomics. 2010 Jun;10(11):2113-22. doi: 10.1002/pmic.200900159.
Recent advances in the speed and sensitivity of mass spectrometers and in analytical methods, the exponential acceleration of computer processing speeds, and the availability of genomic databases from an array of species and protein information databases have led to a deluge of proteomic data. The development of a lab-based automated proteomic software platform for the automated collection, processing, storage, and visualization of expansive proteomic data sets is critically important. The high-throughput autonomous proteomic pipeline described here is designed from the ground up to provide critically important flexibility for diverse proteomic workflows and to streamline the total analysis of a complex proteomic sample. This tool is composed of a software that controls the acquisition of mass spectral data along with automation of post-acquisition tasks such as peptide quantification, clustered MS/MS spectral database searching, statistical validation, and data exploration within a user-configurable lab-based relational database. The software design of high-throughput autonomous proteomic pipeline focuses on accommodating diverse workflows and providing missing software functionality to a wide range of proteomic researchers to accelerate the extraction of biological meaning from immense proteomic data sets. Although individual software modules in our integrated technology platform may have some similarities to existing tools, the true novelty of the approach described here is in the synergistic and flexible combination of these tools to provide an integrated and efficient analysis of proteomic samples.
近年来，质谱仪在速度和灵敏度方面取得了进展，分析方法也有了改进，计算机处理速度呈指数级加速，各种物种的基因组数据库和蛋白质信息数据库也得以普及，这些都导致了大量蛋白质组学数据的产生。因此，开发一个基于实验室的自动化蛋白质组学软件平台，用于自动收集、处理、存储和可视化庞大的蛋白质组学数据集，变得至关重要。这里描述的高通量自主蛋白质组学管道是从底层设计的，为各种蛋白质组学工作流程提供了至关重要的灵活性，并简化了复杂蛋白质组学样本的整体分析。该工具由一个软件组成，该软件控制着质谱数据的获取，并实现了自动执行获取后任务，如肽定量、聚类 MS/MS 光谱数据库搜索、统计验证以及在用户可配置的基于实验室的关系数据库中进行数据探索。高通量自主蛋白质组学管道的软件设计侧重于适应不同的工作流程，并为广泛的蛋白质组学研究人员提供缺失的软件功能，以加速从庞大的蛋白质组学数据集中提取生物学意义。虽然我们集成技术平台中的各个软件模块可能与现有工具具有某些相似之处，但这里描述的方法的真正新颖之处在于这些工具的协同和灵活组合，以提供蛋白质组学样本的综合高效分析。
