Cloud-computing MapReduce toSearch for Post-Translationally Modified Peptides

描述（由申请人提供）：对流行的肽搜索引擎X的增强！提出了Tandem，以允许它在新的超级可伸缩的MapReduce计算机集群上运行。这将允许更快和更便宜的操作，允许蛋白质组学研究人员常规搜索翻译后修饰（PTMs）。蛋白质组学在生物学理解方面取得了许多重要进展。然而，许多有价值的数据集没有被搜索到ptm，仅仅是因为进行搜索所必需的计算机能力是不可用的。在这个项目中，我们计划通过在高度可扩展的计算机集群上运行的肽搜索引擎，大幅降低蛋白质组学实验的计算成本。研究团队完全有资格承担这项研究，在所有科学学科和必要的特定软件元素方面拥有广泛而直接的经验。研究团队包括蛋白质组学、质谱、肽搜索、云计算和MapReduce方面的专家。

DESCRIPTION (provided by applicant): A enhancement to the popular peptide search engine X!Tandem is proposed, to allow it to run on new super-scalable MapReduce computer clusters. This will allow much faster and less-expensive operation, allowing proteomics researchers to routinely search for post-translational modifications (PTMs). Proteomics has led to many important advances in biological understanding. Yet, many valuable data sets are not searched for PTMs, simply because the computer power necessary to conduct the searches is not available. With this project, we plan to substantially reduce the computational cost of proteomics experiments, via a peptide search engine operating on highly-scalable computer clusters. The research team is well-qualified to undertake this research, having extensive, direct experience in all the scientific disciplines and specific software elements necessary. The research team includes experts in proteomics, mass spectrometry, peptide search, cloud computing, and MapReduce. PUBLIC HEALTH RELEVANCE: High-throughput analysis of post-translational modifications is increasingly pivotal for understanding the molecular function and dynamics of living cells. This proposal thus addresses key opportunities for applying proteomics to human health research.