DEVELOPMENT OF PTMAP20 FOR GENOME-WIDE PROTEIN POSTTRANSLATIONAL MODIFICATION

用于全基因组蛋白质翻译后修饰的 PTMAP20 的开发

• 批准号: 7956366
• 负责人: YINGMING ZHAO
• 金额: $ 0.08万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7956366
• 关键词: Biomedical Research; Cells; Chemicals; Computer Retrieval of Information on Scientific Projects Database; Computers; Data; Development; Funding; Goals; Grant; High Performance Computing; Institution; Mass Spectrum Analysis; Modification; Post-Translational Protein Processing; Proteins; Research; Research Personnel; Resources; Software Tools; Source; System; United States National Institutes of Health; abstracting; genome-wide; parallel computing; protein function; tool

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. No Abstract AvailablePosttranslational modifications (PTMs) are essential for protein functions in cell. Mass spectrometry is capable to identify PTMs with high sensitivity comparing to traditional chemical approach. We have developed a new software tool, called PTMap, that is capable to identify all-types of PTMs in a single protein from mass spectrometry data. Here, we propose to combine PTMap with the powerful computer clusters from Teragrid system and extend PTM analysis by PTMap through large-scale parallel computation. Our goal is to develop PTMap2.0 tool for a genome-wide characterization of protein posttranslational modifications.

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 翻译后修饰(PTM)是细胞内蛋白质功能所必需的。与传统的化学方法相比，质谱法能够以较高的灵敏度鉴定PTMS。我们已经开发了一种名为PTMap的新软件工具，它能够从质谱学数据中识别单个蛋白质中的所有类型的PTM。在这里，我们提出将PTMap与TeraGrid系统强大的计算机集群相结合，通过大规模的并行计算来扩展PTMap的PTM分析。我们的目标是开发PTMap2.0工具，用于描述蛋白质翻译后修饰的全基因组特征。