CENTER FOR COMPUTATIONAL MASS-SPECTROMETRY

计算质谱中心

• 批准号: 8362973
• 负责人: Pavel A Pevzner
• 金额: $ 105.24万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8362973
• 关键词: Address; Affect; Antibiotics; Antibodies; Area; Bacteria; Biological Markers; Biotechnology; Blood Clot; Blood coagulation; Cataract; Chimeric Proteins; Collaborations; Communities; Complex; Computer software; Data; Development; Education; Educational Activities; Funding; Generations; Germany; Goals; Grant; Institutes; Institution; International; Malignant Neoplasms; Mass Spectrum Analysis; Mutation; National Center for Research Resources; Pathway interactions; Pharmaceutical Preparations; Post-Translational Protein Processing; Postdoctoral Fellow; Principal Investigator; Protein Databases; Proteome; Proteomics; Research; Research Activity; Research Infrastructure; Research Personnel; Resources; Scientist; Singapore; Snake Venoms; Software Tools; Source; Spain; Students; Sweden; Technology; United Kingdom; United States National Institutes of Health; University Hospitals; aged; computerized tools; cost; design; influenza virus vaccine; instrumentation; programs; symposium

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. DESCRIPTION (provided by applicant): This application seeks support for a center of excellence in computational mass spectrometry and a national and international resource in the broad area of proteomics. It proposes to enlarge the current research activities, to branch into previously unexplored areas of computational proteomics, and to support multiple collaborative efforts. The proposal addresses the computational bottleneck that affects the entire proteomics community and impairs interpretation of data in thousands of experimental labs around the world. The goal is to bring the modern algorithmic technologies to mass-spectrometry and to build a new generation of reliable open access software tools to support both new development in mass-spectrometry instrumentation and the emerging applications of mass-spectrometry. The proposal focuses on four directions: (i) enabling complex mass spectrometry searches, (ii) analyzing unknown proteomes without protein databases, (iii) analyzing altered proteomes, and (iv) constructing proteogenomic annotations and analyzing pathways. These directions cover both well-studied but still inadequately addressed problems (like search for mutations and post-translational modifications) and unexplored problems for which there are no computational tools currently available (like antibody sequencing or analyzing fusion proteins in cancer). These projects require two-way collaborative efforts on a wide range of topics involving biomedical and computational scientists from various institutions. While many collaborations have been already established at San Diego (UCSD and Burnham Institute), sixteen other US universities, hospitals and biotechnology companies, as well as foreign research institutions at Germany, Singapore, Spain, Sweden, and United Kingdom, we propose to further extend these collaborations by developing robust open access mass spectrometry software that will catalyze the exchanges between experimental and computational researchers in proteomics. The biomedical applications addressed in these collaborative projects include but are not limited to (i) discovery of cancer biomarkers, (ii) elucidation of changes in aged cataractous lens, (iii) understanding how bacteria adjust to antibiotics and other harsh conditions, (iv) addressing the need to constantly reformulate the influenza vaccine to make it efficient, and (v) sequencing of snake venoms that proved instrumental in design of blood clotting drugs. Educational activities in the area of computational proteomics will also be developed, including short courses, a seminar program, an annual conference, and concerted education of students and postdocs.

该子项目是利用资源的众多研究子项目之一 由 NIH/NCRR 资助的中心拨款提供。子项目的主要支持 并且子项目的主要研究者可能是由其他来源提供的， 包括其他 NIH 来源。 子项目可能列出的总成本 代表子项目使用的中心基础设施的估计数量， NCRR 赠款不直接向子项目或子项目工作人员提供资金。 描述（由申请人提供）：本申请寻求计算质谱卓越中心以及蛋白质组学广泛领域的国家和国际资源的支持。它建议扩大当前的研究活动，扩展到以前未探索的计算蛋白质组学领域，并支持多项合作努力。该提案解决了影响整个蛋白质组学界并损害全球数千个实验实验室数据解释的计算瓶颈。目标是将现代算法技术引入质谱，并构建新一代可靠的开放获取软件工具，以支持质谱仪器的新发展和质谱的新兴应用。该提案侧重于四个方向：（i）实现复杂的质谱搜索，（ii）在没有蛋白质数据库的情况下分析未知的蛋白质组，（iii）分析改变的蛋白质组，以及（iv）构建蛋白质组注释和分析途径。这些方向涵盖了经过充分研究但仍未充分解决的问题（例如寻找突变和翻译后修饰）以及目前没有可用计算工具的未探索问题（例如抗体测序或分析癌症中的融合蛋白）。这些项目需要在广泛的主题上进行双向合作，涉及来自不同机构的生物医学和计算科学家。虽然圣地亚哥（加州大学圣地亚哥分校和伯纳姆研究所）、其他十六所美国大学、医院和生物技术公司以及德国、新加坡、西班牙、瑞典和英国的外国研究机构已经建立了许多合作关系，但我们建议进一步通过开发强大的开放获取质谱软件来扩展这些合作，该软件将促进蛋白质组学实验和计算研究人员之间的交流。这些合作项目涉及的生物医学应用包括但不限于（i）发现癌症生物标志物，（ii）阐明老化白内障晶状体的变化，（iii）了解细菌如何适应抗生素和其他恶劣条件，（iv）解决不断重新配制流感疫苗以提高其效率的需要，以及（v）对蛇毒进行测序，这被证明有助于设计凝血药物。还将开展计算蛋白质组学领域的教育活动，包括短期课程、研讨会计划、年度会议以及学生和博士后的协调教育。