GENOME ANNOTATION BY MASS SPECTROMETRY

通过质谱进行基因组注释

• 批准号: 7957688
• 负责人: JOHN L YATES
• 金额: $ 0.33万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7957688
• 关键词: Animal Model; Bioinformatics; Biological; Biology; Computer Retrieval of Information on Scientific Projects Database; Funding; Fungal Genome; Genome; Grant; Institution; Mass Spectrum Analysis; Organism; Protein Databases; Proteome; Research; Research Personnel; Resources; Sea Anemones; Source; United States National Institutes of Health; protein complex

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. Currently, high-throughput mass spectrometry requires the existence of curated protein-databases and thereby excludes a growing number of model organisms for which the genome has been sequenced, but not yet annotated. A new experimental approach is therefore developed that aims at covering new proteomes fast, and comprehensively, and independently of how well the particular genome is annotated. To prove the validity of this concept, we apply whole proteome mass spectrometry to an emerging model organism, the starlet sea anemone Nematostella vectensis. The newly developed bioinformatics strategy will represent a computational and biological framework for the analysis of truly complex protein mixtures from organisms with a not yet or incompletely annotated genome.

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。 目前，高通量质谱法需要存在策划的蛋白质数据库，从而排除了越来越多的模式生物，其基因组已被测序，但尚未注释。因此，开发了一种新的实验方法，旨在快速，全面地覆盖新的蛋白质组，并且独立于特定基因组的注释程度。为了证明这一概念的有效性，我们应用全蛋白质组质谱一个新兴的模式生物，星海葵Nematostella vectensis。新开发的生物信息学策略将代表一个计算和生物学框架，用于分析来自尚未或不完全注释基因组的生物体的真正复杂的蛋白质混合物。