CENTER FOR COMPUTATIONAL MASS-SPECTROMETRY

计算质谱中心

• 批准号: 7722705
• 负责人: Pavel A Pevzner
• 金额: $ 98.59万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-20 至 2009-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7722705
• 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; Condition; 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; Range; 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.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 描述（由申请人提供）：本申请为计算质谱卓越中心以及广泛蛋白质组学领域的国家和国际资源提供支持。它建议扩大当前的研究活动，分支为以前未开发的计算蛋白质组学领域，并支持多种协作努力。该提案解决了影响整个蛋白质组学社区的计算瓶颈，并损害了世界上数千个实验实验室中对数据的解释。目的是将现代算法技术带入质量光谱法，并建立新一代可靠的开放式软件工具，以支持质谱仪器中的新开发以及质谱法的新兴应用。该提案的重点是四个方向：（i）启用复杂的质谱搜索，（ii）分析没有蛋白质数据库的未知蛋白质组织，（iii）分析改变的蛋白质组，以及（iv）构建蛋白质组学注释并分析途径。这些方向涵盖了精心研究但仍然不充分解决问题（例如寻找突变和翻译后修饰），也涵盖了目前没有可用的计算工具（例如抗体测序或分析癌症中的融合蛋白）的未开发问题。这些项目需要在涉及来自各个机构的生物医学和计算科学家的广泛主题上进行双向合作努力。虽然已经在圣地亚哥（UCSD和伯纳姆研究所）建立了许多合作，但美国其他16个大学，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，我们建议通过努力进行开放式批量生产和核心群体的交流，以进一步扩展这些协作，以促进质量群体的核心研究，以促进质量相关性和计算机的交流。这些协作项目中针对的生物医学应用包括但不限于（i）发现癌症生物标志物，（ii）阐明衰老白内障镜头变化的变化，（iii）细菌如何适应抗生素和其他恶劣条件，（iv）需要不断地解决启动疫苗的启动，并在启动效果上进行启动，并有效地进行了效率，并有效地启动了有效的效果，并需要进行效率高效的效果，并需要进行效率高效的效果，并需要进行效率高效的效果。血液凝结药物的设计。还将开发计算蛋白质组学领域的教育活动，包括短课程，研讨会计划，年度会议以及对学生和博士后的协调教育。