CENTER FOR COMPUTATIONAL MASS-SPECTROMETRY

计算质谱中心

• 批准号: 8170951
• 负责人: Pavel A Pevzner
• 金额: $ 106.3万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170951
• 关键词: Address; Affect; Antibiotics; Antibodies; Area; Bacteria; Biological Markers; Biotechnology; Blood Clot; Blood coagulation; Cataract; Chimeric Proteins; Collaborations; Communities; Complex; Computer Retrieval of Information on Scientific Projects Database; Computer software; Data; Development; Education; Educational Activities; Funding; Generations; Germany; Goals; Grant; Institutes; Institution; International; Malignant Neoplasms; Mass Spectrum Analysis; Mutation; Pathway interactions; Pharmaceutical Preparations; Post-Translational Protein Processing; Protein Databases; Proteome; Proteomics; Research; Research Activity; 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; 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. 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. 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.

这个子项目是许多利用 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。 描述（由申请人提供）：本申请寻求对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。它建议扩大目前的研究活动，分支到以前未开发的领域的计算蛋白质组学，并支持多个合作的努力。该提案解决了影响整个蛋白质组学社区的计算瓶颈，并损害了世界各地数千个实验室的数据解释。我们的目标是将现代算法技术引入质谱分析，并建立新一代可靠的开放获取软件工具，以支持质谱分析仪器的新发展和质谱分析的新兴应用。该提案侧重于四个方向：（i）实现复杂的质谱搜索，（ii）分析未知的蛋白质组，而没有蛋白质数据库，（iii）分析改变的蛋白质组，（iv）构建蛋白质基因组注释和分析途径。这些方向涵盖了研究充分但尚未充分解决的问题（如寻找突变和翻译后修饰）和目前没有可用计算工具的未探索问题（如抗体测序或分析癌症中的融合蛋白）。这些项目需要来自不同机构的生物医学和计算科学家就广泛的主题进行双向合作。虽然在圣地亚哥已经建立了许多合作关系（加州大学圣地亚哥分校和伯纳姆研究所），其他16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，我们建议通过开发强大的开放获取质谱软件来进一步扩展这些合作，该软件将促进实验和计算研究人员之间的交流，蛋白质组学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）阐明老年白内障透镜的变化，（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使其有效的需求，以及（v）蛇毒的测序，其被证明在凝血药物的设计中是有用的。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。