CENTER FOR COMPUTATIONAL MASS-SPECTROMETRY

计算质谱中心

• 批准号: 7957331
• 负责人: Pavel A Pevzner
• 金额: $ 77.63万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7957331
• 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.

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 描述(由申请人提供)：本申请寻求支持一个计算质谱学的卓越中心和一个广泛的蛋白质组学领域的国内和国际资源。它建议扩大目前的研究活动，分支到以前未探索的计算蛋白质组学领域，并支持多种合作努力。该提案解决了影响整个蛋白质组学社区的计算瓶颈，并损害了世界各地数千个实验实验室的数据解释。其目标是将现代算法技术引入质谱学，并建立新一代可靠的开放获取软件工具，以支持质谱学仪器的新发展和质谱学的新兴应用。该建议集中在四个方向：(I)实现复杂的质谱学搜索，(Ii)在没有蛋白质数据库的情况下分析未知蛋白质组，(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。这些方向既涵盖了研究得很好但仍未充分解决的问题(如寻找突变和翻译后修饰)，也涵盖了目前尚无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)。这些项目需要在广泛的主题上进行双向合作，包括来自不同机构的生物医学和计算科学家。虽然圣地亚哥(加州大学圣迭戈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已经建立了许多合作关系，但我们建议通过开发强大的开放获取质谱学软件来进一步扩大这些合作，该软件将促进蛋白质组学实验研究人员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)发现癌症生物标记物，(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使其有效的需求，以及(V)对蛇毒进行测序，事实证明这对凝血药物的设计起到了重要作用。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、年度会议以及对学生和博士后的协调教育。